This presentation of the original ASC Glossary is meant to augment the lexical resources on cybernetics and systems theory already available online.

THE ASC GLOSSARY

ADAPTATION

a form of behavior is adaptive if it maintains the
essential variables within physiological limits. For example,
the amount of carbon dioxide in the blood is important in its
effect on the blood's alkalinity. If the amount rises, the rate
and depth of respiration are increased, and carbon dioxide is
exhaled at an increased rate. If the amount falls, the reaction
is reversed. By this means the alkalinity of the blood is kept
within limits.

The retina works best at a certain intensity of
illumination. In bright light the nervous system contracts the
pupil, and in dim relaxes it. Thus the amount of light entering
the eye is maintained within limits.

When dry food is chewed, a copious supply of saliva is
poured into the mouth. Saliva lubricates the food and converts
it from a harsh and abrasive texture to one which can be chewed
without injury. The secretion therefore keeps the frictional
stresses below the destructive level.

Many more examples could be given, but all can be included
within the same formula. Some external disturbance tends to
drive an essential variable outside its normal limits; but the
commencing change itself activates a mechanism that opposes the
external disturbance. By this mechanism the essential variable
is maintained within limits much narrower than would occur if the
external disturbance were unopposed. The narrowing is the
objective manifestation of the mechanism's adaptation.

Just the same criterion for adaptation may be used in
judging the behavior of the free-living animal in its learned
reactions. Take the type-problem of the kitten and the fire.
When the kitten first approaches an open fire, it may paw at the
fire as if at a mouse, or it may crouch down and start to 'stalk'
the fire, or it may attempt to sniff at the fire, or it may walk
unconcernedly on to it. Every one of these actions is liable to
lead to the animal's being burned. Equally the kitten, if it is
cold, may sit far from the fire and thus stay cold. The kitten's
behavior cannot be called adapted, for the temperature of its
skin is not kept within normal limits. The animal, in other
words, is not acting homeostatically for skin temperature.
Contrast this behavior with that of the experienced cat: on a
cold day it approaches the fire to a distance adjusted so that
the skin temperature is neither too hot nor too cold. If the
fire burns fiercer, the cat will move away until the skin is
again warmed to a moderate degree. If the fire burns low the cat
will move nearer. If a red-hot coal drops from the fire the cat
takes such action as will keep the skin temperature within normal
limits. Without making any inquiry at this stage into what has
happened to the kitten's brain, we can at least say that whereas
at first the kitten's behavior was not homeostatic for skin
temperature, it has now become so. Such behavior is 'adapted':
it preserves the life of the animal by keeping the essential
variables within limits. (Ashby, 1960, pp. 58, 60-62)

ADIABATIC

occurring without loss or gain of heat. (Webster's)

A FORTIORIANALYSIS

A fortiori analysis is a method of
treating uncertainty that stacks the cards against one
ALTERNATIVE (often the one intuitively preferred) by resolving
questions of uncertainty in favor of another alternative. If the
initially preferred alternative is still preferable, one has a
stronger case in its favor. See also: SENSITIVITY ANALYSIS,
CONTINGENCY ANALYSIS. (IIASA)

ALGEDONICLOOP

a term used by Stafford Beer to describe the
feedback an organism, organization or machine receives from the
environment. The algedonic loop is the large feedback loop that
goes outside the organism and, through reward or punishment,
indicates the environment's response to the organism's behavior.

ALGORITHM

A rule or procedure for solving a recurrent
mathematical problem.

A complete, unambiguous procedure for
solving a specified problem in a finite number of steps.
(Richard Dorf)

Deterministic ALGORITHM: Given the same
input information, will always produce the same output
information, when applied correctly. (John Warfield)

Stochastic ALGORITHM: Given the same information, will not
necessarily produce the same output information, even though
applied correctly. (John Warfield)

Any mechanical or
recursive computational procedure (Dictionary).

ALLOPOIESIS

the process whereby an organization produces
something other than the organization itself. An assembly line
is an example of an allopoietic system. See AUTOPOIESIS.
(Francisco Varela)

ALLOPOIETICMACHINE

Machines that have as a product of their
functioning something different from themselves, as in a car.
(Maturana and Varela, 1979)

ALTERNATIVE

One of the mutually exclusive COURSES OF ACTION
that are considered as means of attaining the OBJECTIVES.
Typically, the alternatives differ in their nature or character,
not only in quantitative details. By mutually exclusive we mean
that the alternatives are competitive in the sense that if A is
selected, B cannot be chosen. A course of action that combines
features selected from both A and B would be a new alternative.
(The synonym "option" is often used in association with the
DECISION MAKER, as in "the decision maker's options were.").
(IIASA)

ANALOGY

correspondence in some respects, especially in
function or position, between things otherwise dissimilar.

a
form of logical inference, or an instance of it, based on the
assumption that if two things are known to be alike in some
respects, then they must be alike in other respects.

ANTICOMMUNICATION

a human relation between persons and things
which emerges and is maintained through messages requiring and
permitting not yet available encoding and decoding systems or
mechanisms. Communication is a human relation between persons
and things which emerges and is maintained through messages
required and permitted by already available encoding and decoding
systems or mechanisms. Communication feeds on an speeds the
decay of information in systems on which depends the significance
of human relations. Anticommunication not only retards this
decay, but even creates systems whose significance depends on
human relations. Insistence on communication ultimately leads to
social and physical violence. Anticommunication ultimately leads
to insistence on composition and peace. (Herbert Brun)

ARTIFICIALINTELLIGENCE

The branch of computer science that
studies how to program computers to exhibit apparently
intelligent behavior. The branches of artificial intelligence
are usually defined as pattern recognition, theorem proving,
language processing, and game playing.

AUTHORITY

power conferred by agreement.

AUTOCATALYTIC

referring to something whose occurrence at one
point increases the probability that it will occur again at
another point. If a property of a system is autocatalytic, then
such a system is, so far as that property is concerned,
essentially unstable in its absence. (Ashby, 1956, p. 196)
Examples: life on the planet Earth, guarantees of civil
liberties in one nation among many, a product for which there is
a demand. (Umpleby)

AUTOLETICS

The psychological principles and processes which
underlie tasks in which performance appears to be self-rewarding.

That is, the task has the property of a goal rather than a means
to a goal. Autotelic tasks are "intrinsically motivated."
"Extrinsically motivated" tasks require external rewards.
(James N. Mosel)

AUTONOMOUS

.independent in governing; mathematically when no
factor in an equation contains time as an explicit variable.
(Iberall)

AUTONOMY

the condition of subordinating all changes to the
maintenance of the organization. Self-asserting capacity of
living systems to maintain their identity through the active
compensation of deformations. (Maturana and Varela, 1979)

AUTOPOIESIS

the process whereby an organization produces
itself. An autopoietic organization is an autonomous and
self-maintaining unity which contains component-producing
processes. The components, through their interaction, generate
recursively the same network of processes which produced them.
An autopoietic system is operationally closed and structurally
state determined with no apparent inputs and outputs. A cell, an
organism, and perhaps a corporation are examples of autopoietic
systems. See ALLOPOIESIS. (Francisco Varela)

AUTOPOIETICMACHINE

a machine organized (defined as a unity)
as a network of processes of production, transformation and
destruction of components that produces the components which: i)
through their interactions and transformations regenerate and
realize the network of processes (relations) that produced them;
and ii) constitute it as a concrete unity in the space in which
they exist by specifying the topological domain of its
realization as such a network. (Maturana and Varela, 1979)

AUTOPOIETICSPACE

an autopoietic organization constitutes a
closed domain of relations specified only with respect to the
autopoietic organization that these relations constitute, and
thus it defines a space in which it can be realized as a concrete
system, a space whose dimensions are the relations of production
of the components that realize it. (Maturana and Varela, 1979)

AXIOLOGY

A branch of philosophy dealing with values, i.e.,
ethics, aesthetics, religion. Based on the Greek for "worth."

The study of the nature of types of and criteria of values
and of value judgments, especially in ethics (John Warfield)

The general theory of value; the study of objects of
interest. (Lotze)

BACK CHANNELCOMMUNICATION

communication which travels through
informal rather than formal channels. Governments and players in
bureaucracies use back channel or informal communication to test
reactions while maintaining deniability. (Prouty)

BEHAVIOR

any sequence of states of a system. (Ashby,
Handout, 1961)

The behavior of a system is overt and thus
manifested in input-output relationships, whereas state
trajectories are covert and must either be inferred or must be
obtained by "opening the black box". (Michael Arbib)

BIFURCATION

a bifurcation is the appearance of an additional
pattern of behavior or sequence of states for a system.
Generally we have successive bifurcations where we increase the
value of some characteristic parameter. One can think of a
per-son traveling down a road. The farther the traveler goes,
the more side streets or alternative routes appear. In a sense
the bifurcation introduces history. To know the state of a
system at any time implies a knowledge of the paths taken or not
taken. (Umpleby after Prigogine, 1980, pp. 105-6)

BIOLOGICAL EXPLANATION

a reformulation in terms of processes
subordinated to autopoiesis, that is a reformulation in the
biological phenomenological domain. (Maturana and Varela, 1979)

BIOLOGICAL PHENOMENON

the biological phenomenology is the
phenomenology of autopoietic systems in the physical space and a
phenomenon is a biological phenomenon only to the extent that it
depends in one way or another on the autopoiesis of one or more
physical autopoietic unities. (Maturana and Varela, 1979)

BIONICS

an attempt to develop better machines through
understanding of biological design principles. (DeGreene in
Beishon and Peters, 3rd edition, pp. 92 and 94)

BORSODI's LAW

as the cost of production diminishes because of
centralized operation, the cost of processing and distribution
increases disproportionately. This law is prevalent especially
for bulky and perishable commodities like foodstuffs, and where
the fixed capital investment can be relatively low in proportion
to the product as in natural farming. (Paul Goodman, "Notes on
Decentralization," in BEYOND LEFT AND RIGHT).

BOUNDARY

The minimum description required to distinguish a
system from its environment. (John Warfield)

BRAIN THEORY

The use of mathematics and computer simulation to
analyze brain function. (Arbib)

BUREAUCRATICBALANCE OFPOWER PRINCIPLE

when a conflict over
alternative policy proposals arises, they tend to be evaluated on
the basis of the extent to which they imply an alteration in the
relative power positions of the various subsystems affected. That
decision is favored which least disrupts the existing balance of
power among the subsystems. (Wheeler, 1970, p.133)

CHANNELCAPACITY

very similar to INFORMATION PROCESSING
CAPABILITY; the number of messages per unit time handled by
either a link or a node (system, element). The messages
transmitted may be either similar or different. It is usually
measured in bits per second.

CLOSED SYSTEM

an isolated system having no interaction with an
environment. (Von Bertalanffy, p.3)

CODING

The process of transforming information from one
representation to another. Each way of representing information
is called a code. (Arbib) A notion which represents the
interactions of the observer, not a phenomenon operative in the
observed domain. A mapping of a process that occurs in the space
of autopoiesis onto a process that occurs in the space of human
design (heteropoiesis) and, thus, not a reformulation of the
phenomenon. (Maturana and Varela, 1979)

COGNITIVE DOMAIN

the domain of all the interactions in which
an autopoietic system can enter without loss of identity.
(Maturana and Varela, 1979)

COMBINATORIAL EXPLOSION

Occurs when a huge number of possible
combinations are created by increasing the number of entities
which can be combined--forcing us to consider a constrained set
of possibilities when we consider related problems. (Arbib)

COMMUNICATION

a human relation between persons and things
which emerges and is maintained through messages required and
permitted by already available encoding and decoding systems or
mechanisms. Communication feeds on and speeds the decay of
information in systems on which depends the significance of human
relations. See ANTICOMMUNICATION. (H. Brun)

COMMUNICATIVE DOMAIN

a chain of interlocked interactions such
that although the conduct of each organism in each interaction is
internally determined by its autopoietic organization, this
conduct is for the other organism a source of compensable
deformations. (Maturana and Varela, 1979)

COMPETITION

a type of activity existing among two or more
elements of a system when each is striving to maximize its use of
a finite and/or non-renewable resource. Agricultural land is an
example of a finite, renewable resource. Mineral deposits are
examples of finite, non-renewable resources. Competition for
finite resources tends to accelerate rates of depletion or leads
to overuse (see the tragedy of the commons). Overuse of finite,
renewable resources can be corrected by altering the rewards and
costs of marginal changes in use.

COMPOSITION

the composer's activity and the traces left by it.
The composer's activity is motivated by a wish of bringing about
that which without him and human intent would not happen. In
particular, the composer's activity consists in constructing
contexts, systems, stipulated universes, where in objects and
statements, selected by the composer, not only manifest more than
their mere existence, but have a function or value of sense or
meaning which without his construction they would not have.
Occasionally the composer's activity brings about that which
without him and without human intent could not have happened,
leaving traces which nothing else could have left. The wish
which motivates the composer's activity is motivated by an
exclusively human property which thus exhaustively and
sufficiently defines the term "human": a "need" which is
generated by a want. Among all biological systems only the human
system contains that self-observing dimension when comes, beyond
the system's "need," the system's want to survive. Thence the
want, beyond the "need," of survival, and thus the exclusively
human concept of an intent that would or will retard decay; in
particular the decay of information, the ordering of a system,
any system stipulated, discovered, or dreamed of. (H. Brun)

COMPUTER CONFERENCING

enables humans to conduct a conference
even though widely scattered geographically, by communicating
through a computer network. Each conferee has a MAILBOX--a
reserved section of computer memory--to which messages may be
sent by other conferees from their terminals. In addition to
MESSAGES a computer conferencing system can include CONFERENCES
and NOTEBOOKS. These are different ways of storing comments in
computer memory and controlling who has access to the material.

CONCEPT

a word or phrase used in propositions purporting to
describe real world relationships. Concepts are neither true nor
false, only more or less useful. (Umpleby)

CONSEQUENCE

A consequence is a result of a COURSE OF ACTION
(or of a decision) taken by the DECISION MAKER (Synonym: outcome;
see IMPACT). In analysis, the consequences of a course of action
are determined (predicted) by the use of MODELS. The
consequences that one would like to have, particularly those
that contribute positively to the attainment of OBJECTIVES, are
referred to as [benefits;] the consequences that one would like
to avoid or minimize are costs. The consequences that do not
bear very much on the main objectives and are not evaluated in
the analysis but that may affect the objectives of other groups
of people are referred to as SPILLOVERS or EXTERNALITIES. A
consequence tree is a graph showing what further consequences
will be caused by some direct consequence of a course of action.
For example, one alternative to stimulate the economy may be to
lower taxes. This will result in an increase of average family
income, which will in time influence the number of cars, which
will have an impact on traffic conditions, on environmental
pollution, and so on. In the literature on DECISION THEORY it is
customary to speak about one [multiattribute consequence] of a
course of action instead of saying "the action has several
consequences." Accordingly, the term [single-attribute
consequence] is used when the course of action has only one
consequence that is being considered (e.g., monetary profit).
Within the context of decision theory, attributes are those
features of a consequence that are taken into account in the
evaluation of this consequence by the decision maker. One
speaks, more precisely, about [value-relevant attributes.]
In mathematical formulations one speaks about a mapping from the
space of courses of action (action space) into the space of
consequences (consequence space.) In a deterministic case the
mapping from action space to consequence space is a
point-to-point mapping. This means that a given course of action
has a given and certain consequence. In a case of RISK or
UNCERTAINTY the mapping from action space to consequence space is
a point-to-set mapping; that is, a given course of action may
have any one of the consequences contained in a given set. In
analysis, the mapping from action space to consequence space is
described by a MODEL. (IIASA)

CONSTRAINT

a relation between two sets such that the variety
that exists under one condition is less than the variety that
exists under another. (Ashby, 1956 p. l27) The total variety
possible is defined by the variables which were selected by the
observer. Constraints reduce this variety to the variety actually
observed. As Ashby says, "The cybernetician looks at what does
not happen." The constraints, or the interaction rules operating
over a set of variables, determine what does not happen.
(Umpleby)

CONSTRAINT

.Constraints are limitations imposed by nature or
by man that do not permit certain actions to be taken.
Constraints may mean that certain OBJECTIVES cannot be achieved.
The actions, ALTERNATIVES, CONSEQUENCES, and objectives that are
not precluded by the constraints are referred to as [feasible.]
In a particular analysis study, some constraints may have to be
considered [stiff] or unquestionable, others--from among those
imposed by prior decisions--may be [elastic] or removable if the
analysis proves a good case for it. For example, the natural
water supply in a region is a stiff constraint, while the money
or manpower allocated to fulfill a certain task may be an elastic
constraint. It is useful to distinguish [short-run] and
[long-run] constraints: for example, existing legislation is a
constraint in the short run, but not necessarily in the long run.
In mathematical terms, if the notions of ACTION SPACE,
CONSEQUENCE SPACE, and OBJECTIVE SPACE are introduced, the
constraints determine a [feasible set] in each of those spaces.
(IIASA)

CONTEXT

The material that surrounds an item which helps define
its meaning. (Arbib)

CONTINGENCY ANALYSIS

Contingency analysis is a method of
treating UNCERTAINTY that explores the effect on the
ALTERNATIVES of change in the ENVIRONMENT in which the
alternatives are to function. This is a "what-if" type of
analysis, with the what-ifs being external to the alternative, in
contrast to a SENSITIVITY ANALYSIS, where the parameters of the
alternatives are varied. See also: A FORTIORI ANALYSIS.
(IIASA)

CONTINUUM

a space or field whose elemental parts cannot be
separately discerned at the scale of observation. (Iberall)

CONTROL

Choosing the inputs to a system so as to make the
state or outputs change in (or close to) some desired way.
(Arbib)

COOPERATION

a type of activity existing among two or more
elements of a system when they are engaged in a mutually
beneficial exchange.

CORRESPONDENCE PRINCIPLE

any new theory, whatever its
character--or details--should reduce to the well-established
theory to which it corresponds when the new theory is applied to
the circumstances for which the less general theory is known to
hold. This principle was first applied to the theory of atomic
structure by Niels Bohr in l923. (Weidner and Sells, l960, p. 29)
The principle can be applied to great advantage in relativity
theory and in quantum mechanics. It can also be applied to the
LAW OF REQUISITE VARIETY, the PRINCIPLE OF SELF-ORGANIZATION, and
the more recent interpretations of the possibility of
objectivity. (Umpleby)

COUPLED

When mechanisms or functional subsystems are connected
causally to influence each other, they are said to be coupled.
If A is causally connected to B, the connection is often
described by coupling coefficients or influence coefficients.
(Iberall)

COUPLING(OF UNITIES)

whenever the conduct of two or more
unities is such that the conduct of each one is a function of the
conduct of the others. (Maturana and Varela, 1979)

COURSE OF ACTION

A means available to the DECISION MAKER by
which the OBJECTIVES may be attained. A SYSTEMS ANALYSIS usually
considers several possible courses of action, which are then
referred to as ALTERNATIVES or as the decision maker's OPTIONS.
(IIASA)

CREOD

derived from the Greek words for "necessity" and "a
path." A term coined by D.S. Waddington who says a creod is a
"time trajectory of developmental change (arising) from the
characteristics of the closed circular causal organization of the
system of genes and cytoplasm. Creods are a type of phenomena
which occurs in many other fields also." (Waddington, 1960, p.
82)

CRITERION

A criterion is a rule or standard by which to rank
the ALTERNATIVES in order of desirability. The use of
"criterion" to mean "objective" is incorrect. See OBJECTIVE.
(IIASA)

CYBERNETICS

The science of communication and control in
animal and machine.

Perhaps because the field is still
young, there are many definitions of cybernetics. Norbert
Wiener, a mathematician, engineer and social philosopher, coined
the word "cybernetics" from the Greek word meaning steersman. He
defined it as the science of communication and control in the
animal and the machine. Ampere, before, him, wanted cybernetics
to be the science of government. For philosopher Warren
McCulloch, cybernetics was an experimental epistemology concerned
with the communication within an observer and between the
observer and his environment. Stafford Beer, a management
consultant, defined cybernetics as the science of effective
organization. Anthropologist Gregory Bateson noted that whereas
previous sciences dealt with matter and energy, the new science
of cybernetics focuses on form and pattern.

A way of looking
at things and a language for expressing what one sees (Margaret
Mead)

CYBORG

an organism with a machine built into it with
consequent modification of function;

an organism which is
part animal and part machine. Since some theorists regard
organisms as biological machines, we must define our terms
further. An animal will be defined as a creature whose elements
are the result of "small loop autopoiesis." That is the creature
creates itself but the parts are the result of localized
processes. Mind is not involved in the production of the parts.
Mind results from the functioning of the parts but is manifested
in the external behavior of the organism. A cyborg, then, is a
creature composed of some parts constructed without the benefit
of mind and some parts constructed with the benefit of mind.
Furthermore the parts must be of greater than molecular size. A
creature with aspirin in its body is not a cyborg. A creature
with an artificial heart is a cyborg. Under this definition,
animals with donated hearts, kidneys or retinas would also be
cyborgs. (Umpleby)

DECENTRALIZED GOVERNMENT

A form of government with its
top-level decision-making processes dispersed throughout the
system rather than concentrated in one person, place or
legislative body. (Arbib)

DECISION MAKER

A decision maker is a person, or group of
people (e.g., a committee), who makes the final choice among the
ALTERNATIVES. Synonym: decision taker. (IIASA)

DECISION THEORY

Decision theory is a body of knowledge and
related analytical techniques of different degrees of formality
designed to help a DECISION MAKER choose among a set of
ALTERNATIVES in light of their possible CONSEQUENCES. Decision
theory can apply to conditions of certainty, RISK, or
UNCERTAINTY. [DECISION UNDER CERTAINTY] means that each
alternative leads to one and only one consequence, and a choice
among alternatives is equivalent to a choice among consequences.
In [DECISION UNDER RISK] each alternative will have one of
several possible consequences, and the probability of occurrence
for each consequence is known. Therefore, each alternative is
associated with a probability distribution, and a choice among
probability distributions. When the probability distributions
are unknown, one speaks about [DECISION UNDER UNCERTAINTY.]
Decision theory recognizes that the ranking produced by using a
CRITERION has to be consistent with the decision maker's
OBJECTIVES and preferences. The theory offers a rich collection
of techniques and procedures to reveal preferences and to
introduce them into MODELS of decision. It is not concerned with
defining objectives, designing the alternatives or assessing the
consequences; it usually considers them as given from outside, or
previously determined. Given a set of alternatives, a set of
consequences, and a correspondence between those sets, decision
theory offers conceptually simple procedures for choice. In a
decision situation under certainty the decision maker's
preferences are simulated by a single-attribute or
MULTIATTRIBUTE VALUE FUNCTION that introduces ordering on the
set of consequences and thus also ranks the alternatives.
Decision theory for risk conditions is based on the concept of
utility (see UTILITY, sense 2). The decision maker's
preferences for the mutually exclusive consequences of an
alternative are described by a UTILITY FUNCTION that permits
calculation of the EXPECTED UTILITY for each alternative. The
alternative with the highest expected utility is considered the
most preferable. For the case of uncertainty, decision theory
offers two main approaches. The first exploits criteria of
choice developed in a broader context by GAME THEORY, as for
example the [MAX-MIN RULE,] where we choose the alternative such
that the worst possible consequence of the chosen alternative is
better than (or equal to) the best possible consequence of any
other alternative. The second approach is to reduce the
uncertainty case to the case of risk by using SUBJECTIVE
PROBABILITIES, based on expert assessments or on analysis of
previous decisions made in similar circumstances. See also:
GAME THEORY, OPTIMIZATION, UTILITY, VALUE (IIASA)

DELPHI METHOD

A group communication structure used to
facilitate communication on a specific task. The method usually
involves anonymity of responses, feedback to the group as a whole
of individual and/or collective views and the opportunity for any
respondent to modify an earlier judgment. The method is usually
conducted asyncronously via paper and mail but can be executed
within a computerized conferencing environment. At the essence
of the method is the question of how best to tailor the
communication process to suit the situation. The Delphi method
was originally developed at the RAND Corporation by Olaf Helmer
and Norman Dalkey. (Murray Turoff)

A technique to arrive at
a group position regarding an issue under investigation, the
Delphi method consists of a series of repeated interrogations,
usually by means of questionnaires, of a group of individuals
whose opinions or judgments are of interest. After the initial
interrogation of each individual, each subsequent interrogation
is accompanied by information regarding the preceding round of
replies, usually presented anonymously. The individual is thus
encouraged to reconsider and, if appropriate, to change his
previous reply in light of the replies of other members of the
group. After two or three rounds, the group position is
determined by averaging. (IIASA)

DEMAND

As a term in economics, demand means the amount of
a commodity (good or service) that would be purchased at a given
price. An associated term is [DEMAND FUNCTION,] which presents
the demand-versus-price relationship. A demand function for a
given commodity is compared with a corresponding [SUPPLY
FUNCTION] to determine the EQUILIBRIUM PRICE: a price at which
the supply offered matches the demand.

In another usage,
demand means the amount of a commodity required for a certain
purpose. It often relates to the future, as in: "the world
energy demand in the year 2030 will be 35 terawatts." Implicit
in this statement is that the price of energy as well as other
economic conditions will be such that 35 terawatts will be
consumed (purchased) if technically available. (IIASA)

DIALECTIC

The Hegelian method of logic, based on the concept
of advancing contradictory arguments, of thesis and antithesis,
and seeking their resolution by synthesis. (Iberall)

DIFFUSION

the spread of an idea, product or process beyond
first use. (Umpleby)

DISCOUNT RATE

It is assumed that a monetary unit received
today is worth more than a monetary unit to be received a year
from now. This assumption requires that, in order to determine
the present value of future sums, the analyst use an interest
rate to discount these future sums. If i is the assumed annual
interest or discount rate, expressed as a decimal, the present
value of x monetary units to be received in n years from now is
given by the formula:

Present value = X
------
(l+i)n

Discount rates are used when comparing alternatives that differ
in the time-character of their flows of COSTS and BENEFITS; to
compare them, costs and benefits are discounted to the same year.
There are no clear-cut rules as to what an appropriate discount
rate should be in a given case.

DISCOUNTING

The process by which most people place a heavy
emphasis on the present and very near future and by which events
not in the present or very near future are not considered
important for consideration, i.e., are discounted. (Rogers)

DIVERSITY

variations in the mode in which identity is
maintained. (Maturana and Varela, 1979)

DOMAIN

Generally a limited region or field marked by some
specific property. In mathematics, it can have a somewhat more
specialized meaning. (Iberall)

DOMINANCE

An ALTERNATIVE is said to be dominant with respect
to a second alternative whenever one or more of the CONSEQUENCES
of the first are superior (i.e., preferred according to some
CRITERION) to the corresponding consequences of the second, and
all others are equally valued. (IIASA)

ECONOMY OF SCALE

Relative saving realized when the size of a
plant, enterprise, etc., is increased. For example, lower
production cost of an automobile due to production of a large
number of cars of the same type is due to economy of scale.
There may also exist a DISECONOMY OF SCALE where the increased
size contributes to an increase in unit cost.

EFFECTIVENESS

In SYSTEMS ANALYSIS, the effectiveness of an
ALTERNATIVE is usually represented by an aggregative expression
approximating the totality of output or performance aspects of
that alternative that are relevant to goal attainment. Ideally,
it is a single quantitative measure that can be used to evaluate
the performance level achieved in attaining the OBJECTIVES.
(IIASA)

An absolute measure of performance. (Turoff)

EFFICIENCY

Program A is said to be more efficient than
program B if, for a given cost, a chosen aggregated measure of
its positive results (such as EFFECTIVENESS or BENEFIT) is
greater than that for program B. (IIASA)

A ratio scale
measurement of a measure of performance to resources expended to
obtain the level of performance. (Turoff)

ENSEMBLE

An aggregation or collection of elements connected by
a series of relations. (Iberall)

ENTROPY

unavailable energy or molecular disorder. Entropy is
at a maximum when the molecules in a gas are at the same energy
level. Entropy should not be confused with uncertainty.
Uncertainty is at a minimum when all elements are in the same
category. (Umpleby)

ENVIRONMENT

Environment is most often used as a synonym of
state of nature, a concept useful in modeling. It embraces all
external factors or forces that are beyond the influence of the
DECISION MAKER but nevertheless affect the CONSEQUENCES of his
action. Environment is also occasionally used as a synonym of
STATE OF THE WORLD. The difference between the two concepts is
that state of the world can include the consequences of a course
of action as well as the external factors, while the state of
nature comprises the external factors only (IIASA)

EPIGENETIC

Related to the doctrine that the entity that will
develop into a viable system (e.g., the germ cell developing into
an organism) is acted upon and depends both on the conditions in
its environment as well as its internal coding (i.e., it is both
the phenotype and genotype that determines the emergence of the
living organism). (Iberall)

EQUIFINALITY

a condition in which different initial conditions
led to similar effects. (see MULTIFINALITY.) Equifinality in
biological systems led the German biologist Driesch to embrace
vitalism--the doctrine that vital phenomena are inexplicable in
terms of natural science. (Von Bertalanffy, p. 40)

EQUILIBRIUM

a condition characterized by a balance of forces.
(Umpleby)

ERGODIC

of or relating to a process in which a sequence or
sizable sample is equally representative of the whole (as in
regard to a statistical parameter);

involving or relating to
the probability that any state will recur, especially having zero
probability that any state will never recur. (WEBSTER'S
DICTIONARY)

ERGODIC

A collection of systems forms an ergodic ensemble if
the modes of behavior found in any one system from time to time
resemble its behavior at other temporal periods and if the
behavior of any other system when chosen at random also is like
the one system. We do not require identical performance, only
quite similar time averages and number averages. (If you cannot
tell one youth from another or one adult from another, they
belong to an ergodic ensemble.) In an ergodic population, any
single individual is representative of the entire population.
The salient characteristics of this individual are essentially
identical with any other member of the group. (Iberall)

ETHOLOGY

The newer definition relates to the study of animal
behavior, founded on a comparative zoological and physiological
base. (Iberall)

EUDEMONY

a measure of the more preferred state of affairs; the
commodity that the control system tends to optimize. The
eudemony concern is one of values, of stating what is worth
optimizing; in short, eudemony is a category of outcomes that
indicate we are enhancing the quality of life. (Beer, PLATFORM
FOR CHANGE, p. l59)

EVALUATION

Evaluation as used in a technical sense in the
United States means assessment of a government program's past or
ongoing performance. The key issue in PROGRAM EVALUATION is to
determine the extent to which the program, rather than other
factors, has caused any changes that have been observed. (IIASA)

EVIDENCE

a configuration (a human made image) of reality used
and an "argument" in support of the reality of this
configuration. I use the word "evidence" only rarely, and then
with embarrassment. Samefacedly I am forced to admit that I am a
member, and speak the languages, of such societies as must not
yet be encouraged to waive the "argument" and to deal directly
with the configuration as the only reality worth dealing with.
Not yet: because "evidence," now, is reality against change, and
change, now, reality against "evidence." Shamefacedly: because,
as long as the word which I wish to define, defines me, I cannot
define it, without defining myself, whom I desire to be defined
quite differently. Worth dealing with: because, even then,
"truth" would not be. I wish I could use the word "evidence"
whenever I wish to speak of "desires" fulfilled, and the
consequences, as "arguments" for or against the desirability of
the fulfillment. (H. Brun)

EVOLUTION

A process of continuous change from a lower,
simpler, or worse, to a higher, more complex, or better state; a
process of change in some direction. (Webster's)

The coming
into being of a new and higher order process. (Laszlo)

The
development of each species from different, usually simpler
ancestral forms. The more similar are two species, the closer in
time are they likely to be to a common ancestor. (Arbib)

history of change in the realization of an invariant organization
embodied in independent unities sequentially generated through
reproductive steps, in which the particular structural
realization of each unity arises as a modification of the
preceding one (or ones) which, thus, constitutes both its
sequential and historical antecedent. (Maturana and Varela, 1979)

EXPANSIONISM

A doctrine that maintains that all objects,
events and experiences are parts of larger wholes. Expansionism
is another way of viewing things, a way that is different from,
but compatible with, reductionism. (Ackoff, l974, p. l2)

EXPERIMENTATION

In SYSTEMS ANALYSIS, experimentation is the
process of determining the results of a proposed COURSE OF ACTION
or program by conducting an experiment on a smaller scale in
which the course of action is applied to a sample drawn from the
future target group. An example would be a test of a new health
policy in a restricted region instead of the whole country, or a
test on a randomly selected sample of the population. The
results are best when the experiment is controlled--i.e., when
the test and control groups are chosen before program
implementation in such a way that they are as similar as
possible. In this way, any differences that are observed during
the experiment can be ascribed to the program. Experimentation is
used whenever current knowledge and understanding of factors such
as social attitudes and group preferences are not sufficient to
provide dependable model-based predictions. (See: MODEL)
(IIASA)

EXPLANATION

a reformulation of a phenomenon in such a way that
its elements appear operationally connected in its generation.
(Maturana and Varela, 1979)

EXTERNALITY

An externality is a CONSEQUENCE not considered in
analysis. An externality that affects the interests of other
groups of people or other DECISION MAKERS is referred to as a
SPILLOVER. If the effects of an externality are appreciable, it
may have to be taken into account (internalized) in the analysis.
The term externality derives from economics, where externalities
are costs or benefits not taken into account in a transaction or
system of transactions. For example, the cost borne by others
when an industry pollutes a stream would be referred to as an
externality. (IIASA)

FAIL SAFE

a property of a system in which failure is
impossible. See SAFE FAIL.

FEEDBACK

information about the results of a process which is
used to change the process itself. Negative feedback reduces the
error or deviation from a goal state. Positive feedback
increases the deviation from an initial state. (Umpleby)

FLUCTUATION

the change in some physical quantity in time,
particularly if it varies around some average value for the
quantity. (Iberall)

FORECAST

A forecast is a statement, usually in probabilistic
terms, about the future state or properties of a system based on
a known past and present. A CONDITIONAL FORECAST states in
probabilistic terms what the future will be if a course of action
is taken. A forecast that states with a high degree of
confidence what the future will be is referred to as a
PREDICTION. A forecast that is a hypothesis rather than a
formally justified inference from past data is referred to as a
SCENARIO. Forecasting techniques range from expert judgments to
mathematical forecasting MODELS. The FORECASTING LEAD
(forecasting horizon) is the length of time ahead of now for
which one can make a reasonable forecast. It depends, in the
general sense, on available data. A forecast that makes itself
come true is referred to as a SELF- FULFILLING FORECAST. For
example, a forecast for the rapid growth of a certain city may
encourage business to locate there, thus causing the forecast to
be realized. (IIASA)

FREEDOM

Every social system grants its members some freedom.
Freedom consists of the kind and number of alternatives open for
choice to its members. However, every choice made leads to a
loss of freedom: the structure of these systems tends, in
consequence of the choice made to render at least some not chosen
alternatives, from then on, inaccessible to the members who made
the choice. The freedom granted therefore reduces the freedom of
those of its members who use it. Choice results in loss of
freedom. Loss of freedom can only be prevented by a society so
structured, that it would remain desirable to its members, even
if, therein, the freedom of choice were never to reduce, at least
to preserve, and often to increase, the number of alternatives
open for choice. (H. Brun)

FUNCTION

Metaphor, that image which determines another
image. (Rogers)

An association of a certain object(s) from
one set with each object from another set (mathematics).
(Rogers)

The normal or characteristic action of a system of
entities, generally in time. (Iberall)

The variation of
some magnitude that depends upon the variation of some other
magnitude. (Iberall)

a notion that arises in the
description made by the observer of the components of a machine
or system in reference to an encompassing entity, which may be
the whole machine or part of it and whose states constitute the
goal that the changes in the components are to bring about.
(Maturana and Varela, 1979)

GAME

a set of moves which are defined by a set of rules
limiting what the players may do. A game may or may not be a
simulation. A game does not necessarily involve a representation
of events in a reference system. (Umpleby)

GAME THEORY

Game theory is a branch of mathematical analysis
developed to study decision making in conflict situations. Such
a situation exists when two or more DECISION MAKERS who have
different OBJECTIVES act on the same system or share the same
resources. There are two person and multiperson games. Game
theory provides a mathematical process for selecting an OPTIMUM
STRATEGY (that is, an optimum decision or a sequence of
decisions) in the face of an opponent who has a strategy of his
own.

In game theory one usually makes the following assumptions:

Each decision maker ["PLAYER"] has available to him two or
more well-specified choices or sequences of choices (called
"PLAYS").

Every possible combination of plays available to the players
leads to a well-defined end-state (win, loss, or draw) that
terminates the game.

A specified payoff for each player is associated with each
end-state (a [ZERO-SUM GAME] means that the sum of payoffs to
all players is zero in each end-state).

Each decision maker has perfect knowledge of the game and of
his opposition; that is, he knows in full detail the rules of the
game as well as the payoffs of all other players.

All decision makers are rational; that is, each player,
given two alternatives, will select the one that yields him the
greater payoff.

The last two assumptions, in particular, restrict the
application of game theory in real-world conflict situations.
Nonetheless, game theory has provided a means for analyzing many
problems of interest in economics, management science, and other
fields. (IIASA)

GESTALT

A structure, configuration, or pattern of
physical, biological, sociological, or psychological phenomena so
integrated as to constitute a functional unit with properties not
derivable from its parts in summation. This German word is
considered by many system thinkers (e.g., von Bertalanffy,
Angyal) to convey more accurately the concept of organized wholes
than the word system. (Steven Rogers)

The organized
structure or pattern that makes up all of a person's experience
of some system. This integrated view is more than the sum of the
individual elements by which the field can be described.
(Iberall)

GOAL

End toward which effort is directed. (Webster's)

A statement, expressed in the following form: To (Action Word)
(Object) (Qualifying Phrase). (John Warfield)

A preferred
outcome in a particular situation that can be obtained within a
specified time period. (Ackoff)

An end state consciously
selected a priori. (Larry Richards)

GOAL SEEKING

the process of arriving at a goal once it has
been defined. (Umpleby)

GOALFORMULATION

the process of deciding what the next goal to
be sought will be. (Umpleby)

HERMENEUTIC

interpretive; explanatory.

HERMENEUTICS

plural in form, used with a singular verb. The
science and methodology of interpretation, especially of
Scriptural text. From the Greek "to interpret."

HETEROPOIESIS

the space of human design. (Maturana and Varela,
1979)

HETERARCHY

a form of organization resembling a network or
fishnet. Authority is determined by knowledge and function. See
HIERARCHY. (Umpleby)

HEURISTIC

Characterizing a system in which the internal
parameters can be changed when necessary through feedback.

A
heuristic idea serves as a guide for discovery. It serves as a
valuable aid for empirical research but may be unproved or
incapable of proof. (Umpleby)

HEURISTIC

An aid to discovery, any device or procedure used to
reduce problem-solving effort, a rule of thumb.

HIERARCHY

A form of organization resembling a pyramid.
Each level is subordinate to the one above it. See HETERARCHY.
(Umpleby)

An organization whose components are arranged in
levels from a top level down to a bottom level. (Arbib)

A
partially-ordered structure of entities in which every entity but
one is successor to at least one other entity; and every entity
except the basic entities is a predecessor to at least one other
entity. (Rogers)

Narrowly, a group arranged in order of
rank or class; we interpret it to denote a rank arrangement in
which the nature of function at each higher level becomes more
broadly embracing than at the lower level. (Iberall)

HISTORICAL PHENOMENON

a process of change in which each state
of the successive states of a changing system arises as a
modification of a previous state in a causal transformation and
not de novo as an independent occurrence. (Maturana and Varela,
1979)

HOLISM

the process of focusing attention directly on the whole
and its characteristics as a whole, without any recourse to
consideration of its parts. (Sahal, in FUTURE DIRECTIONS, or
Lendaris and Wakeland, "Structural Modeling - A Bird's Eye View")

HOMEOSTASIS

Dynamic self-regulation.

The condition of
a system when it is able to maintain its essential variables
within limits acceptable to its own structure in the face of
unexpected disturbances. The concept was formulated by W.B.
Cannon in 1929-32.

HOMEOSTAT

a machine built by Ross Ashby in the l940's to
demonstrate the behavior of an ULTRASTABLE SYSTEM. For a
description, see Chapter 8 of Ashby, 1960.

HOMEOSTATICMACHINES

machines which display the condition of
maintaining constant or within a limited range of values some of
their variables. (Maturana and Varela, 1979)

HOMOMORPHISM

similarity of external form, appearance or size.

IDEOGRAPHY

the representation of ideas by graphic symbols.

the use of ideograms to express ideas.

IMPACT

Impact is used in three different ways:

as
synonymous with CONSEQUENCE;

to mean any consequence
(beneficial or adverse) that reaches beyond the direct purpose of
a given COURSE OF ACTION, as in: "the impact of the new steel
plant on employment opportunities in the region;"

as in
(2), but the meaning restricted to adverse consequences, as in
"the impact of industrial growth on the ecological environment."
(IIASA)

IMPLEMENTATION

Implementation means the process of carrying
out a course of action. Implementation starts at the decision
and terminates when the objectives are attained. (IIASA)

INDIVIDUALITY

maintenance of identity by an autopoietic
machine independently from its interactions with an observer.
(Maturana and Varela, 1979)

INFORMATION

that which reduces UNCERTAINTY. (Claude
Shannon);

that which changes us. (Gregory Bateson)

INFORMATION ENVIRONMENT

the messages, symbols, meanings, that
a person encounters in an average day through conversations with
other persons and through the media. People inhabiting nearly
the same physical environment can live in very different
information environments. An example would be people working on
a university campus or in an international organization.

INPUT

an event external to a system which modifies the system
in any manner.

INPUT-OUTPUT(LEONTIEF)ANALYSIS

Input-output (Leontief)
analysis is a technique developed for quantitatively analyzing
the interdependence of producing and consuming units in an
economy. Input-output analysis studies the interrelations among
producers as buyers of each other's outputs, as users of
resources, and as sellers to final consumers. For example, if a
planner wishes to expand the activities of some industry, or some
component of final consumption, an input-output analysis can tell
what amount of other manufactured goods, resources, and labor
this requires. In an INPUT-OUTPUT MODEL the output product of
each sector of the economy is set equal to the input consumption
of that product by other industries plus the consumption by
final consumers. All inputs and outputs are expressed in the
same units (usually in monetary units per unit of time, for
example in schillings/year). One denotes Aij the worth of output
product of sector i required as input by sector j to produce one
unit's worth of its product. Then, if we denote Xl, X2,..Xn
the output products of the sectors, the basic relation of the
MODEL is:

N
Xi = SUM Aij Xj + Yi
J=l

where Yi is the consumption of product i by final consumers. In
a model with three sectors, we have, for example, for the output
product X2:

X2 = A2l Xl + A22 X3 + Y2

>which reads: "out of the total output X2 the amount A2l Xl is
used by sector l to produce output Xl,..., and the amount Y2 is
consumed by final consumers." The parameters Aij are referred to
as TECHNOLOGICAL COEFFICIENTS. They are usually arranged into a
table called the TECHNOLOGICAL INTERDEPENDENCE MATRIX for the
system being modeled. (IIASA)

INQUIRING SYSTEM

An orderly and fully developed procedure or
plan for investigation. Philosophically, a way of looking at
reality. Frequently used to describe the formal methodologies
of the major philosophers. The term implies adherence to rigid
set of procedures that are uniquely derived from a single,
fundamental concept of reality. (Example: one who believes that
truth and knowledge are only derived from experience would base
an investigation upon experimental procedures and would not rely
upon analysis or synthesis to extrapolate from one piece of
knowledge to another.) (Mitroff and Turoff)

INTELLIGENCE

Appropriate selection. (Ross Ashby)

INTUITION

The immediate knowing or learning of something
without the conscious use of reasoning. (Webster's)

In its
cognitive function it is a psychic organ or means to apprehend
reality. It is a synthetic function in the sense that it
apprehends the totality of a given situation or psychological
reality. It does not work from the part to the whole -- as the
analytical mind does -- but apprehends a totality directly in its
living existence. (Assagioli)

It is by logic that we prove,
but by intuition that we discover. (Poincare, CY sq.)

ISOMORPHIC

Having the same or similar form; we have
interpreted this more broadly to represent similarity in both
form and function. (Iberall)

ISOMORPHISM

A mapping of one entity into another having
the same elemental structure, whereby the behaviors of the two
entities are identically describable. (John Warfield)

A
formal correspondence of general principles or even of special
laws. (Bertalanffy)

A set of principles may be transferred
from one field to another without need to duplicate the effort.
(Weinberg)

a one-to-one correspondence between the elements
of two sets such that the result of an operation on elements of
one set corresponds to the result of the analogous operation on
their images in the other set.

ITERATIVE PROCESS

An iterative process is a process for
calculating a desired result by means of a repeated cycle of
operations. An iterative process should be convergent, i.e., it
should come closer to the desired result as the number of
iterations increases.

JUMP PHENOMENA

In many fields, there are surfaces of
discontinuity on both sides of which the field phenomena change
drastically. The change in conditions between the two sides is
said to be described as a jump and represents jump phenomena.
(Iberall)

KLUGE

something not designed as a whole but rather put
together from available parts. The term if frequently used by
engineers. Marvin Minsky has described the human brain as a
kluge.

LANGUAGE

A systematic way of arranging symbols, usually to
express meaning. It may be a NATURAL LANGUAGE like Chinese,
English or Swahili that humans use to communicate with one
another, or a PROGRAMMING LANGUAGE in which programs are written
for a computer. (Arbib)

LAW OF REGULATORY MODELS

every good regulator of a system must
be (contain) a model of that system. (Conant and Ashby, 1982)

LAW OF REQUISITE VARIETY

the amount of appropriate
selection that can be performed is limited by the amount of
information available.

for appropriate regulation the
variety in the regulator must be equal to or greater than the
variety in the system being regulated. Or, the greater the
variety within a system, the greater its ability to reduce
variety in its environment through regulation. Only variety (in
the regulator) can destroy variety (in the system being
regulated). The law was formulated by Ross Ashby. (Umpleby)

LIMIT CYCLE

In a linear system (such as a vibrating string or
a pendulum), if the system is displaced (pluck the string), it
will start to vibrate or oscillate. However, according to the
second law of thermodynamics the system will decay to rest. In a
nonlinear system (examples: a watch, a human, a working engine)
supplied with a constant source of fuel or energy, it is possible
to obtain configurations such that if the system is started
vibrating, oscillating, or running, it will continue. If the
cycle thus formed operates independent of the precise initial
starting conditions, in spite of the fact that the system is
loggy and in spite of moderate disturbances that tend to slow the
process down or speed it up, then it is said to be a limit cycle.
(Iberall)

LINGUISTIC DOMAIN

a consensual domain in which the coupled
organisms orient each other in their internally determined
behavior through interactions that have been specified during
their coupled ontogenies. (Maturana and Varela, 1979)

LINGUISTICS

The study of language. This includes the study of
syntax -- what it is that makes a sentence well-formed -- and of
semantics -- how the words of a sentence work together to give
the sentence its overall meaning. Parsing is the process of
breaking a string of words into the constituents specified by the
syntax. (Arbib)

MACHINE

a state-determined system; any system showing
behavior such that the specification of a state determines the
subsequent state; a set of states closed under a mapping. (Ashby,
Handout, l96l)

a unity in the physical space, defined by its
organization, which connotes a non-animistic outlook, and whose
dynamisms are apparent. (Maturana and Varela, 1979)

MACHINEWITH INPUT

any machine in which part of the state
vector is regarded as under exterior control (the input) and part
inaccessible (the internal state) such that for any pairing of
input and internal state, the subsequent internal state is
determined. (Ashby, Handout, l96l)

MACHINEPURPOSE OR AIM OF

the use to which a machine can be
put by man, sometimes its product. A descriptive device to
reduce the task of conveying to a listener the organization of a
particular machine. (Maturana and Varela, 1979)

MARGINAL EFFECTIVENESS

ratio of the increase in performance
due to an increase in the resources expended. (Turoff)

MARKOVIANMACHINE

a probabilistic machine; any system showing
behavior such that the probability (frequency) of any given state
determines the probability (frequency) of the subsequent state;
any machine in which the states are given as probabilities.
(Ashby, Handout, l96l)

MECHANICAL PHENOMENOLOGY

the phenomenology generated by
relations between processes realized through the properties of
components. (Maturana and Varela, 1979)

MECHANISM

a biological outlook which asserts that the only
factors operating in the organization of living systems are
physical factors, and that no non-material vital organizing force
is necessary. (Maturana and Varela, 1979)

MEDIATE

To be the intermediate mechanism for bringing about
change or providing communication; i.e., to manipulate to new
operating conditions. (Iberall)

METAPHOR

a figure of speech in which a term is transferred
from the object it ordinarily designates to an object it may
designate only by implicit comparison or by analogy, as in the
phrase "evening of life."

META-SYSTEM

a system acts according to its own nature and for
the purpose defined by that nature. A child is playing: he
attempts to poke scissors into the electric power points; he
makes interesting ink-patterns on the carpet; he attempts to
drink from the liquid detergent container. All of these
activities arise directly from the nature of the system: child -
exploration -environment. Fortunately there is another system
which lies outside the child system. This outside or meta-system
operates according to its own nature which is child care.
Primitive tribes quickly establish a system of beliefs, taboos
and laws. Without this meta-system everyone would act according
to their own individual systems which might be based on immediate
gratification, self-indulgence and impulse. The meta- system
lies outside these individual systems and overrides them in favor
of society and a longer time base. For example, an individual
may only collect enough food for his immediate needs but the
meta-system may require him to collect enough to store for the
winter as well. To some extent, the success of societies has
depended on the strength, and the nature, of the meta-systems
they have set up. An individual goes to see a psychoanalyst and
is told that his troubles arise from the way his mother treated
him when he was young. This explanation or 'story' becomes a
meta-system for the individual and can explain or guide his
actions independently of his mood of the moment. Religion is the
prime example of a meta-system that has served to override man's
small view of himself and given him aims and values he might not
otherwise have developed. The internal logic of the religious
meta-system is based on its own nature,and not on the needs of
man. Outside religions, strictly so called ideologies,
philosophies and moral concepts have also served as meta-systems.
(De Bono)

METHODOLOGY

The systematic analysis and organization of the
rational and experimental principles and processes which must
guide a scientific inquiry, or which constitute the structure of
the sciences more particularly. Methodology is a generic term
exemplified in the specific method of each discipline and its
full significance can be understood only by analyzing the
structure of each discipline. In determining that structure, one
must consider

(a) the proper object of the discipline,

(b) the manner in which
it develops,

(c) the type of statements or generalizations it
involves,

(d) its philosophical foundations or assumptions, and

(e) its relation with other disciplines and eventually its
applications. (Dict. of Philosophy)

A methodology is a kind of
"coaching" -- not a formula for producing a result, but a set of
practices that can lead to appropriate questioning and to
appropriate change. (Winograd and Flores, 1987)

MICROWORLD

a limited "world" - such as the subject matter of a
specialized data base - that restricts the semantics of a
computer program for planning or natural language understanding.
(Arbib)

MILIEU

Surroundings, environment, in the sense of a
fluid-like environment in which many diverse species or biota are
immersed. (Iberall)

MINIMAX PRINCIPLE

in situations with conflicting alternatives,
the most rational strategy is the one that promises to minimize
the maximum possible losses.

MODEL

a set of propositions or equations describing in
simplified form some aspects of our experience. Every model is
based upon a theory, but the theory may not be stated in concise
form. (Umpleby)

MODEL

An object or process which shares crucial properties of
an original, modeled object or process, but is easier to
manipulate or understand. A SCALE MODEL has the same appearance
as the original save for size and detail. However, increasing
use is made of COMPUTER SIMULATION: the model is a program that
enables a computer to determine how key properties of the
original will change over time. It is easier to change a program
than to rebuild a scale model if we want to explore the effect of
changes in policy or design. (Arbib)

MODEL

A model is a device, scheme, or procedure typically used
in SYSTEMS ANALYSIS to predict the CONSEQUENCES of a COURSE OF
ACTION; a model usually aspires to represent the real world (to
the degree needed in analysis)--for example, a relation between
some observed phenomena. A model can be FORMAL (e.g., a
mathematical expression, a diagram, a table) or JUDGMENTAL (e.g.,
as formed by the deductions and assessments contained in the mind
of an expert). Some models are CAUSAL -- i.e., they reflect
cause-effect relationships. Others are CORRELATIONAL MODELS
which do not necessarily reveal whether some of the observed
phenomena are the cause of the others. An example is correlation
models used for weather forecasting; note that the farmer who
predicts rain on the basis of some observed phenomena and his
past experience is using a judgmental correlation model. A
DETERMINISTIC MODEL generates the response to a given input by
one fixed law; a STOCHASTIC MODEL picks up the response from a
set of possible responses according to a fixed probability
distribution (stochastic models are used to simulate the behavior
of real systems under random conditions). A DYNAMIC MODEL can
describe the time-spread phenomena (dynamic processes) in a
system. A STATIC MODEL describes the system at a given instant of
time and in an assumed state of equilibrium. Among the formal,
mathematical models an ANALYTIC MODEL is formed by explicit
equations. It may permit an analytic or numerical solution. An
analytic model is LINEAR if all equations in the model are
linear. We speak of a SIMULATION MODEL if the solution, i.e.,
the answer to the question which the analyst has posed, is
obtained by experiments on the model rather than by an explicit
solution algorithm. A typical example is STOCHASTIC SIMULATION,
where one wants to obtain probabilistic properties of a system's
response by evaluating the results of a large number of
simulation runs on the model. In some analyses the model by
which one predicts the outcome of a course of action must take
into account that this outcome depends also on actions taken by
other decision makers. If the assumption can be made that those
decision makers optimize some defined objective functions, and
all the other aspects of the system can also be formalized, an
OPTIMIZATION MODEL (e.g., a linear programming model) can be used
to determine the system's response to a course of action. In
ROLE-PLAYING MODELS those decision makers (and perhaps some other
elements of the system as well) are simulated by human actors. In
a MAN-MACHINE MODEL an actor or actors play roles while other
parts of the model are implemented on a computer. A formal model
has a STRUCTURE (the form of an equation, for example) and
PARAMETERS (the value of coefficients in an equation for
example). Determination of both the structure and parameters is
MODEL IDENTIFICATION; determination of the parameters on the
basis of experimental data is MODEL ESTIMATION. The check of a
proposed model against experimental data other than those used
for parameter estimation is model VALIDATION. See also
VERIFICATION. (IIASA)

MODEL OF THE WORLD

The information that an animal or robot has
stored about the world around it. It thus serves to guide the
system's interaction with its environment. (Arbib)

MORPHOGENESIS

evolutionary development of the structure of
an organism or part.

embryological development of the
structure of an organism or part.

The process in complex
system-environment exchanges that tends to elaborate a system's
given form or structure. Examples are the growth of an animal
from a fertilized ovum, biological evolution, learning, and
societal development. A morphogenic system is capable of
maintaining its continuity and integrity by changing essential
aspects of its structure or organization. (Von Bertalanffy,
GST, pp. 148-9)

See AUTOPOIESIS.

MORPHOLOGY

The study of
structure or form and the features comprised in the form and
structure of an organism or any of its parts, in which a
definite behavioral approach is employed and a specific
methodology is used. (John Warfield)

MORPHOSTASIS

the process in complex system-environment
exchanges that tends to serve or maintain a system's given form,
organization, or state. Examples are homeostatic processes in
organisms, and ritual in socio-cultural systems.

MULTIFINALITY

a condition in which similar initial conditions
lead to different end effects.

MULTISTABLESYSTEM

within a multistable system, subsystem
adapts to subsystem in exactly the same way as an animal adapts
to its environment.

The environment is assumed to consist of
large numbers of subsystems that have many states of equilibrium.
The environment is thus assumed to be polystable.

Whether
because the primary joins between the subsystems are few, or
because equilibria in the subsystem are common, the interaction
between subsystems is assumed to be weak.

The organism
coupled to this environment will adapt by the basic method of
ultrastability, i.e., by providing second-order feedbacks that
veto all states of equilibrium except those that leave each
essential variable within its proper limits.

The organism's
reacting part is itself divided into subsystems between which
there is no direct connection. Each subsystem is assumed to have
its own essential variables and second order feedback. To trace
the behavior of the multistable system, suppose that we are
observing two of the subsystems, e.g., A and B and that their
main variables are directly linked so that changes of either
immediately affect the other, and that for some reason all the
other subsystems are inactive. The first point to notice is that,
as the other subsystems are inactive, their presence may be
ignored; for they become like the 'background'. Even some are
active, they can still be ignored if the two observed subsystems
are separated from them by a wall of inactive subsystems.
The next point to notice is that the two subsystems, regarded as
a unit, form a whole which is ultrastable. This whole will
therefore proceed, through the usual series of events, to a
terminal pattern of behavior. If, however, we regard the same
series of events as occurring, not within one ultrastable whole,
but as interactions between a minor environment and a minor
organism, each of two subsystems, then we shall observe
behaviors homologous with those observed when interaction occurs
between 'organism' and 'environment'. Trial and error will
appear to be used; and, when the process is completed, the
activities of the two parts will show co-ordination to the
common end of maintaining the essential variables of the double
system within their proper limits. Exactly the same principle
governs the interactions between three subsystems. If the three
are in continuous interaction, they form a single ultrastable
system which will have the usual properties. As illustration, we
can take the interesting case in which two of them, A and C say,
while having no immediate connection with each other, are joined
to an intervening system B, intermittently but not
simultaneously. Suppose B interacts first with A: by their
ultrastability they will arrive at a terminal pattern of
behavior. Next B and C interact. If B's step-mechanisms,
together with those of C, give a stable pattern of behavior to
the main variables of B and C, then that set of B's
step-mechanism values will persist indefinitely; for when B
rejoins A the original stable pattern of behavior will be
re-formed. But if B's set with C's does not give stability, then
it will be changed to another set. It follows that B's
step-mechanisms will stop changing when, and only when, they have
a set of values which forms fields stable with both A and C.
(Ashby, l960, pp. 208-2l0)

NECESSITY

refers to the urgency with which one wishes to
establish a relation or connection found missing. (H. Brun)

NEED

a condition which must be met continuously and
unconditionally if living organisms are to be able to be
motivated to maintain themselves, their identities, their
existence. Continuously: because the conditions continue in
consequence of having been met. Unconditionally: because
without the conditions called "needs" having been met no other
condition exists. (H. Brun)

NET EFFECTIVENESS...VALUE ADDED...NET GAIN

An interval scale
measurement of the difference between the measure of performance
and the resources expended to obtain the level of performance.
(Turoff)

NOISE

refers not simply to audible sound but rather to any
undesired information in a communication channel which is not
part of the intended message. Thus, smudges on a printed page,
static on a radio, "ghosts" on a television can be interpreted as
noise according to this definition. Because noise is an
evaluative term, it occurs only in the receiver. The channel
does not know the difference. (Umpleby)

NORMATIVE

relating to an authoritative standard or principle
of right action binding on the members of a group and serving to
guide, control, or regulate proper and acceptable behavior; a
pattern or trait taken to be typical in the behavior of a social
group. (Umpleby)

OBJECTIVE

An objective is something that a DECISION MAKER
seeks to accomplish or to obtain by means of his decision. A
decision maker may have more than one objective (the
MULTIPLE-OBJECTIVES case).

An objective may be specified in a more or less general
Fashion, may be quantified or not quantified, and is usually part
of a HIERARCHY OF OBJECTIVES. The term GOAL is sometimes used to
denote a very general objective( at the top of the hierarchy) and
TARGET is used to mean a very definite objective. Example: "The
goal of allocating money to the municipality was to increase the
quality of urban life. The immediate objectives were to improve
public transportation and fire services. A 10% reduction of
average travel time from home to work and a 70% decrease of
average alarm-to-action time taken by the fire brigades were set
forth as targets."

The multiple objectives of a single decision maker are
usually COMPETITIVE: i.e. the improvement in one of them is
associated with a deterioration in another (usually because of
limited resources or because of other CONSTRAINTS).
Competitive objectives are sometimes referred to as CONFLICTING
OBJECTIVES. However, one should speak about a conflict and about
conflicting objectives only if there are two or more decision
makers who have different objectives and who act on the same
system or share the same resources. In the example given above,
the director of urban transportation and the director of city
fire services have conflicting objectives. At the same time, the
mayor of the city, if he were the single decision maker, would
look at these objectives as competitive. If the two directors
are left without a coordinating influence by the mayor (who
would, for example, decide how to allocate the resources), a
CONFLICT SITUATION may result. (See GAME THEORY.) With the
mayor's interventions, the system becomes a hierarchy of decision
makers, and the conflict may be resolved. When the extent to
which an objective is attained is measurable on some appropriate
scale, one can speak about the degree of attainment of the
objective. In SYSTEMS ANALYSIS, one often uses [PROXY
OBJECTIVES:] objectives other the original ones, but such that
are measurable and can be quantitatively discussed. A proxy
objective should at least point in the same direction as the
original one; for example, "reduction of mean travel time" in
urban transportation is a proxy for "improved services." In a
mathematical description, the measures of the multiple objectives
Q1, Q2, ...Qn are considered to be coordinates of a point in the
n-dimensional OBJECTIVE SPACE. Then, the TARGET VALUES Tl,
T2,..Tn prescribed for the n objectives are considered to be
coordinates of the TARGET POINT in this space. When the target
value requirements are set forth as some intervals rather than
single Numbers, they define a region in the objective space that
is referred to as a TARGET SET. (IIASA)

OBJECTIVITY

old definition: an observation is considered
objective if the characteristics of the observer do not appear in
the observation. New definition: shared objectivity (Heinz Von
Foerster, l970)

OBSERVER

One who watches without participating.

The
source of factual evidence; a person who communicates his sense
impression of the external environment.

Everything said is
said to an observer. (Witz, in Von Foerster, 1974)

Observer dependence - the concept that knowledge of reality is
dependent upon the perceptions of the observer.

Observer
inseparability - the concept that observation or measurement
affects the state of the object being observed, that is,
objective measurement or observation from outside a system is not
possible, and the act of observing makes the observer part of the
system under study. Therefore, the observer or measuring device
should be included in the definition of the system. (Weinberg)

A system which, through recursive interactions with its own
linguistic states, may always linguistically interact with its
own states as if with representations of its interactions.
(Maturana and Varela, 1979)

OCCAM'S RAZOR

named after William
of Occam. Given a choice between two explanations, choose the
simplest -- the explanation which requires the fewest
assumptions.

ONTOGENY

the history of the structural transformations of a
unity. (Maturana and Varela, 1979)

OPEN SYSTEM

an entity with a boundary that is not closed. It
receives inputs and produces outputs. (Umpleby)

ORGANIZATION

the relations that define a system as a unity,
and determine the dynamics of interaction and transformations
which it may undergo as such a unity, constitute the organization
of a system. (Maturana and Varela, 1979)

Operations research (operational research
in Britain) as understood today is essentially identical to
SYSTEMS ANALYSIS. Historically, it was a narrower area of
activity that stressed quantitative methods and did not concern
itself with TRADEOFFS between OBJECTIVES and means or with
problems of equity. It was defined by the Operational Research
Society of Great Britain as follows (OPERATIONAL RESEARCH
QUARTERLY, l3(3): 282, l962): Operational research is the
attack of modern science on complex problems arising in the
direction and management of large systems of men, machines,
materials and money in industry, business, government and
defense. Its distinctive approach is to develop a scientific
model of the system, incorporating measurements of factors such
as change and risk, with which to predict and compare the
outcomes of alternative decisions, strategies or controls. The
purpose is to help management determine its policy and actions
scientifically. (IIASA)

OPPORTUNITY COST

Opportunity cost is defined as the advantage
forgone as the result of the acceptance of an ALTERNATIVE. It is
measured as the BENEFITS that would result from the next best
alternative use of the same resources that were rejected in favor
of the one accepted. Opportunity cost is difficult, perhaps
impossible, to measure precisely. (IIASA)

OPTIMIZATION

Optimization is an activity that aims at finding
the best (i.e., optimal) solution to a problem. For optimization
to be meaningful there must be an OBJECTIVE FUNCTION (see below)
to be optimized and there must exist more than one FEASIBLE
SOLUTION, i.e., a solution which does not violate the
CONSTRAINTS. The term optimization does not apply, usually , when
the number of solutions permits the best to be chosen by
inspection, using an appropriate CRITERION (see DECISION THEORY).
One distinguishes SINGLE OBJECTIVE and MULTIOBJECTIVE
OPTIMIZATION. In the first case, the objective is SCALAR-VALUED
(it can be measured by a single number); in the second, the
objective is VECTOR-VALUED (its value is expressed by an n-tuple
of numbers). In mathematical terms, the formulation of an
optimization problem involves DECISION VARIABLES, Xl, X2,..Xn,
the OBJECTIVE FUNCTION,

Q = f(Xl,X2,...Xn)

constraint relations, usually of the form

Gi(Xl,X2,.....Xn) greater than or equal to O, i = l,2,.....m.

The OPTIMAL SOLUTION (or "solution to the optimization problem")
is values of decision variables xl, x2,...xn that satisfy the
constraints and for which the objective function attains a
maximum (or a minimum, in a minimization problem). Very few
optimization problems can be solved analytically, that is, by
means of explicit formulae. In most practical cases appropriate
computational techniques of optimization (numerical procedures of
optimization) must be used. Among those techniques LINEAR
PROGRAMMING permits the solution of problems in which the
objective function and all constraint relations are linear.
NONLINEAR PROGRAMMING does not have this restriction, but can
manage many fewer decision variables and constraints. INTEGER
PROGRAMMING serves to solve problems where the decision variables
can take only integer values. STOCHASTIC or PROBABILISTIC
PROGRAMMING must be used for problems where the objective
function or constraint relations contain random-valued parameters
(in the latter case, the problem is referred to as a
CHANGE-CONSTRAINED PROBLEM). A special case is dynamic
optimization problems where the decision variables are not real
numbers or integers but functions of one or more independent
variables -- functions of time or space coordinates, for example.
Dynamic optimization problems are sometimes referred to as
"optimal control problems." There exist special techniques to
solve such problems; they often make use of DISCRETIZATION of the
independent variables, for example dividing the time axis into a
number of intervals and considering the solutions to be constant
over those intervals. A single-objective optimization problem
may have (and usually does have) a single-valued, unique
solution. The solution to a multiobjective problem is, as a
rule, not a particular value, but a set of values of decision
variables such that, for each element in this set, none of the
objective functions can be further increased without a decrease
of some of the remaining object functions (every such value of a
decision variable is referred to as PARETO-OPTIMAL). (IIASA)

OUTPUT

any change produced in the surrounding by a system.
(Umpleby)

PARADIGM

an outstandingly clear or typical example or
archetype. (Webster's)

The total pattern of perceiving,
conceptualizing, acting, validating, and valuing associated with
a particular image of reality that prevails in a science or a
branch of science. (Kuhn)

A theoretical model to explain a
type of social behavior. (Dict. of Anthropology)

PARADOX

a tenet contrary to received opinion; a statement that
is seemingly contradictory or opposed to common sense and yet
perhaps is true; a self- contradictory statement that at first
seems true; an argument that apparently derives
self-contradictory conclusions by valid deduction from acceptable
premises. (Webster's) A paradox is not the same as a
contradiction. "The shirt is blue; the shirt is not blue," and
"It is raining; it is not raining," are examples of
contradictions. A paradox occurs when one makes an assumption
and, following a logical argument, arrives at the converse. A
paradox will always result when one formulates a set that
contains itself. Below are several examples:

Suppose there is a small town that consists only of men.
There are two kinds of men in this town--those who shave
themselves and those who are shaved by the barber. Who shaves
the barber? If he shaves himself, then he is shaved by the
barber. But if he is shaved by the barber, then he shaves
himself. If the barber is assumed to be in one set, he appears
in the other. This situation occurs because the barber both
appears in the set and is used to define the set.

A person from the island of Crete asserts, "All Cretans
are liars." We can conclude that if he is telling the truth,
then he is lying. But if he is lying, then he is telling the
truth. Once again an element of the set is referring to the set.

Consider a businessman accused of accepting a bribe. He
claims, "I did not take the bribe." There are two possible
interpretations of this statement. Either he is a knowledgeable
observer making a correct statement, or he is a knowledgeable
observer lying to avoid going to jail. The businessman is both
the observer and the person being observed. We have no way of
knowing which role he is playing.

As the third example indicates, paradox leads to
"undecidability". When two equally correct interpretations are
possible, in the absence of further information, no decision
other than a random choice is possible. (Umpleby)

PARAMETER

that which determines the structure of a system.
Parameters themselves can be changed by inputs, but usually the
parameters determine how input will be transformed into outputs.
In the linear equation y = ax + b, the slope "a" and the
y-intercept "b" are the parameters; "x" is the independent
variable and "y" the dependent variable. (Umpleby)

In
computer science PARAMETER is an entry in a command or routine
that must be replaced with specific data prior to execution.
(Arbib)

In a system theory PARAMETERS are used to
distinguish between systems that are described by similar sets of
equations--the choice of parameters fits the model to a specific
situation. (Arbib)

The New York Times Magazine of May l3, l979, discusses
definitions of parameter". The shortest one that seems neat:
PARAMETER - that what gives definition. another one: PARAMETER
-a constant whose value may vary. limit combining both:
PARAMETER - a variable that gives definition to a system.

PARETOOPTIMALITY

the "best that could be achieved without
disadvantaging at least one group." (Allan Schick, in Louis C.
Gawthrop, l970, p.32)

PECEPTRON

a machine that determines whether or not an event
fits a certain pattern; a machine that makes decisions by adding
up evidence obtained from many small experiments. (Minsky and
Papert, p. 4)

PERFECT INFORMATION

a characteristic of a situation in which
all data relevant to a problem is known. Numbers are available
for all variables necessary for a solution, through some of the
numbers may be the result of estimates rather than measurements.
"Perfect" in this context refers to completeness with no implied
judgment about quality. (Umpleby)

PHASE PLANE

If a process can be described by two key
variables, then the relationship may be plotted 2 dimensionally -
in the phase plane. (Arbib)

PHENOMENOLOGICALDOMAIN

defined by the properties of the
unity or unities that constitute it, either singly or
collectively through their transformations or interactions. Thus
whenever a unity is defined or a class of unities is established
which can undergo transformations or interactions, a
phenomenological domain is defined. (Maturana and Varela, 1979)

PHENOMENOLOGY

the study of all possible appearances in
human experience, during which considerations of objective
reality and of purely subjective response are temporarily left
out of account.

a philosophical movement based on
phenomenology, originated by Edmund Husserl about 1905.

PHYSICAL SPACE

the space within which the phenomenology of
autopoiesis of living systems takes place. (Maturana and Varela,
1979)

PLANNING

The process of generating and comparing different
courses of action and then choosing one prior to action. It
takes the system from a high-level specification of what is to be
done to a detailed specification of how to do it. (Arbib)

POLYSTABLE SYSTEM

a state-determined system that has partial,
fluctuating, and temporary independencies within the whole. Its
parts have a high proportion of equilibrial states. A polystable
system can be richly joined, so that almost every variable is
joined to almost every other, or it can be poorly joined. A
polystable system midway between the two will show a somewhat
confused picture. Subsystems will be formed with kaleidoscopic
variety and will persist only for short times; some will be
stable for a brief interval, only to be changed and to
disintegrate. The number of stable variables will tend to climb
as a few subsystems become stable, only to fall back by a larger
or smaller amount as they become unstable. The oscillations will
be large until all subsystems become stable at the same time.
Then the system as a whole will remain stable. (Ashby, 1960,
Chapter l3)

POWER

power resides where information resides (McCulloch,
see the PRINCIPLE OF REDUNDANCY OF POTENTIAL COMMAND;

power
is the ability to limit choice. (Von Foerster in the mid
1960's), A does not have power over B unless A is able to
constrain a necessary transaction of B;

a power relationship
requires compliance (Maturana);

power is the consequence,
submission is the cause (von Foerster, 1983).

Indirect or
secondary exercise of power occurs when A constrains the
necessary transactions of C so C will constrain the necessary
transactions of B. A secondary boycott is an example.

Power
distorts information. Hence, the President, who needs to be well
informed, is often poorly informed because his power distorts the
information given to him. No adviser wants to be the bearer of
bad news or news which the President is thought not to want to
hear. Deliberate steps are required to achieve accurate
information.

If one accepts the idea that one is powerless,
then one feels justified in threatening those one defines as
powerful. However, the "powerful" usually feel threatened by the
"powerless" who invariably outnumber them. Threats by the
powerless against the powerful can make the powerful feel that
repression is necessary in order to preserve the safety of
themselves and their families.

PREDICTION

"to predict the future is to perform an operation
on the past," Norbert Wiener. "The essential point is that the
agent in the act of prediction depends wholly on the actual past
and not in the least on the actual future." (Ashby, "Induction,
Prediction, and Decision-Making in Cybernetic Systems")

PRINCIPLE OF COMPARATIVE ADVANTAGE

units of production --
whether people or machines -- will be employed in those processes
in which they are relatively more productive. This is the
standard rebuttal for those who fear that machines will replace
people. The principle implies that both people and machines can
be fully employed regardless of their relative productivity. The
long-run impact of industrialization and automation, it is
argued, is not to reduce the size of the labor force but rather
is to use machines in tasks best performed by machines and to use
people in tasks which can only be done by people. (H. Simon,
1965, p. 6)

PRINCIPLE OF COMPLEMENTARITY

Some observations can never be
made simultaneously. For example, one cannot see an electron as
a particle and a wave at the same time. Two different
experimental situations are necessary, and they cannot be
realized simultaneously. The principle was first formulated by
Niels Bohr. (Lefebvre, 1983, p. xxv)

the fundamental purpose
of a system should not be jeopardized, nor its fundamental
objectives significantly compromised, in order to accommodate
events of extremely low probability. (R. Machol, 1965, pp. l-7)

PRINCIPLE OF THE HUMBLE ELITE

For certain governmental
functions, shining of the function must be handled by experts.
Such an elite must be humble in that it accepts the
responsibility to explain its decisions to the public and be
responsive to their viewpoints. (Arbib)

PRINCIPLE OF LEAST EFFORT

a system will try to adapt to its
environment or will try to change the environment to suit its
needs, whichever is easier. (Umpleby)

PRINCIPLE OF MAXIMAL AUTONOMY

The purpose of a planning
network is to provide tools for local planning, rather than
primarily to provide centralized control of the planning at
different nodes (Arbib)

PRINCIPLE OF PARSIMONYORPRINCIPLE OF SIMPLICITY

a criterion
for deciding among scientific theories or explanations. One
should always choose the simplest explanation of a phenomenon,
the one that requires the fewest leaps of logic. (Umpleby)

PRINCIPLE OF REDUNDANCY OF POTENTIAL COMMAND

power resides
where information resides. (Warren McCulloch)

PRINCIPLE OFSELF-ORGANIZATION

"every isolated, determinant
dynamic system obeying unchanging laws will develop organisms
that are adapted to their environments." "The argument is simple
enough in principle. We start with the fact that systems in
general go to equilibrium. Now most of a system's states are
non-equilibrial

So in going from any state to one of the
equilibria, the system is going from a larger number of states to
a smaller. In this way, it is performing a selection, in the
purely objective sense that it rejects some states, by leaving
them, and retains some other state, by sticking to it. Thus, as
every determinate system goes to equilibrium, so does it select.
We have heard ad nauseam the dictum that a machine cannot select;
the truth is just the opposite; every machine, as it goes to
equilibrium, performs the corresponding act of selection."
(Ashby in W. Buckley (ed.) MODERN SYSTEMS RESEARCH FOR THE
BEHAVIORAL SCIENTIST, P.115)

"A system shows self-organization, if its behavior shows
increasing redundancy with increasing length of the protocol.
Since redundancy may increase either by a reduction of H or an
increase in H max, and since H max may be increased only by a
redefinition of the system (a change in the number of its
states), we may speak of the organization of a system only in the
case where the increase in redundancy results from a decrease in
H. (Ashby, Handout, 1961) See also SELF-ORGANIZING.

PRINCIPLE OF SUBOPTIMIZATION

Optimizing each subsystem
independently will not in general lead to a system optimum, or
more strongly, improvement of a particular subsystem may actually
worsen the overall system. The principle of suboptimization
provides the basis for a link between organizational structure
and the policies adopted. (Machol, 1965, pp. l-8) See also
SUBOPTIMIZATION.

PRINCIPLE OF SUBOPTIMIZATION

The well-being of an element is
dependent on the well-being of the system of which it is a part.
It is sometimes necessary for an element to limit its goals and
actions in order to preserve the well-being of the system. In
acting to achieve its goals one element may come to constrain the
actions of another element to the point of serious injury to the
other element.

PRINCIPLE OF SUBSIDIARITY

problems are best
solved in the subsystem where they arise. This is similar to
the idea of management by exception. Subsystems are encouraged
to resolve their conflicts themselves without referring them to
higher authority. Whatever solution is adopted, the subsystem
will have to carry it out. Since their consent is essential, the
optimum condition is for them to resolve their conflicts
independently. If a solution is worked out by the subsystem,
appeal to authority is not necessary. (Wheeler, 1970, p. l33)

PRINCIPLE OF SUPERPOSITION

if input A produces output B and
input C produces output D, the principle of superposition holds
if input A+C produces output B+D. Otherwise it does not hold. If
the principle of superposition applies, the system is linear.
The superposition principle is the basis for treating all
problems in wave mechanics including interference and
diffraction. It is also fundamental for the analysis of
electronic circuits. (Umpleby)

PRINCIPLE OF UNDIFFERENTIATED ENCODING

the brain does not
perceive light, sound, heat, touch, taste or smell. It receives
only neuronal impulses from sensory organs. Thus the brain does
not "see light," "hear sounds," etc.; it can perceive only "this
much stimulation at this point on my body." The practical
consequence is that all perceptions, let alone "thoughts," are
deductions from sensory stimuli. They cannot be otherwise. All
observations are therefore partly the function of the observer.
This situation renders complete objectivity impossible in
principle. (Heinz Von Foerster, "On Constructing a Reality.")

PROGRAM

A structure of instructions that spells out
step-by-step how a job is to be done by a computer. (Arbib)

PURPOSE

the possession of an internal project or program
represented and realized through the components of a unity.
(Maturana and Varela, 1979)

RECURSION

Defining a program in such a way that it may call
itself, so that use of the program may occur again and again
during its execution. (Arbib)

RECURSION

of, pertaining to, or designating: a) a
mathematical expression, such as a polynomial, each term of which
is determined by application of a formula to preceding terms. b)
a formula that generates the successive terms of such an
expression. From the Latin "a return."

RECURSIVE SYSTEM THEORY

In a recursive organizational
structure any viable system contains, and is contained in a
viable system. (Beer, l977)

REDUCTIONISM

a doctrine that maintains that all objects and
events, their properties, and our experience and knowledge of
them are made up of ultimate elements, indivisible parts.
(Ackoff, l974, p. 8)

REDUNDANCY

one minus the ratio of the actual uncertainty to
the maximum uncertainty. "This is the fraction of the structure
of the message which is determined not by the choice of the
sender, but rather by the accepted statistical rules governing
the choice of the symbols in question." (Shannon and Weaver,
1948, p. l3)

REGULATION

if an environmental variable (such as temperature)
or an input or output variable (such as the flow demand on a
system) changes and the system can nearly compensate for those
changes in some other variable (such as outlet pressure) then the
system is said to be regulated or regulated for that variable.
If the regulation is obtained by a static compensation in which
some linkage or component is introduced that diminishes the
sensitivity to change, then this is static regulation (e.g., a
spring scale is designed with materials that thermally compensate
the spring against temperature change; a dc motor is designed by
the choice of its field windings to give a speed regulation
against changes in the load put on the motor; a chemical buffer
shifts the operating point of chemical equilibrium to hold the pH
of a solution constant). In dynamic regulation, two different
switch states (an "on" and an "off" state) are arranged so that
the system switches from one state to the other when the
regulated parameter rises to an upper limit (an on-off
thermostat). In feedback regulation (or control as it is
technically referred to), an error signal is produced between the
existing state of a system and the desired regulated level. This
error signal is operationally acted upon, amplified in power, and
fed to an actuator to operate a network which can influence the
regulated variable so as to reduce the error, e.g., in biology
the Na+ angiotension system. The signal is the sodium
concentration. When this concentration decreases, aldosterone is
liberated from the adrenal cortex. This agent acts on the kidney
distal cubules to increase the reabsorption of sodium ions and
re-establish the proper concentration of sodium. (Iberall)

a
notion valid in the domain of description of heteropoiesis, that
reflects the simultaneous observation and description made by
the designer (or its equivalent) of interdependent transitions
of the system that occur in a specified order and at specified
speeds. (Maturana and Varela, 1979)

REGULATOR

a system which
determines (selects) and enforces (maintains) the operating
parameters of another system. The regulator may or may not be a
subsystem of the system being regulated. (Umpleby)

REGULATOR

something that blocks the flow of variety from
disturbances to essential variables. If an automatic pilot is a
good regulator, the passengers will have a smooth flight whatever
the gustiness outside. They will, in short, be prevented from
knowing whether or not it is gusty outside. Thus a good pilot
acts as a barrier against the transmission of information.
The same argument applies to an air-conditioner. If I live in an
air-conditioned room, and can tell, by the hotness of the room,
that it is getting hot outside, then that conditioner is failing
as a regulator. If it is really good, and the blinds are drawn,
I shall be unable to form any idea of what the outside weather is
like. The good conditioner blocks the flow inwards of
information about the weather. The same thesis applies to the
higher regulations achieved by such activities as hunting for
food and earning one's daily bread. Thus while the unskilled
hunter or earner, in difficult times, will starve and will force
his liver and tissues (the essential variables) to extreme and
perhaps unphysiological states, the skilled hunter or earner will
go through the same difficult times with his liver and tissues
never taken to extremes. In other words, his skill as a regulator
is shown by the fact, among others, that it prevents information
about the times reaching the essential variables. In the same
way, the skilled provider for a family may go through difficult
times without his family realizing that anything unusual has
happened. (Ashby, l956, pp. 200-20l)

REIFICATION

treatment of an analytic or abstract relationship
as though it were a concrete entity. (Young, p. l09)

RELATIONS OF CONSTITUTION

determine that the components
produced constitute the topology in which the autopoiesis is
realized. (Maturana and Varela, 1979)

RELATIONS OF ORDER

determine that the concatenation of the
components in the relations of constitution, specification and
order be the ones specified by the autopoiesis. (Maturana and
Varela, 1979)

RELATIONS OF SPECIFICITY

determine that the components
produced be the specific ones defined by their participation in
the autopoiesis. (Maturana and Varela, 1979)

REPRODUCTION

any of the processes of replication, copying or
self-production. (Maturana and Varela, 1979)

RESILIENCE

The measure of a system's ability to remain
within a domain of stability in response to fluctuations of the
system by a disturbance, and the ability of the system to return
to that stable domain having once left. (Holling)

The
ability of a system to make a smooth transition to a new stable
state in response to changes in external conditions. The wider
the range of external fluctuations in which the system can obtain
a stable state, the greater is the resiliency of the system.
(Turoff) See also STABILITY.

a measure of the ability of a
system to absorb changes and still persist. (Holling)

RESOURCE ANALYSIS

The process of determining the economic
resource IMPACTS of alternative proposals for future COURSES OF
ACTION. While in resource analysis, physical quantities are
often ultimately translated into monetary terms, the real aim is
to measure the probable "resource drain" on the economy that
would result from various possible actions. The resource analyst
must not only give attention to economic costs but also has to
determine if it is feasible to obtain needed physical material
and manpower in the required time period. (IIASA)

RISK

In DECISION THEORY and in statistics, risk means
UNCERTAINTY for which the probability distribution is known.
Accordingly, [RISK ANALYSIS] means a study to determine the
outcomes of decisions along with their probabilities -- for
example, answering the question: "What is the likelihood of
achieving a l,000,000 schilling profit in this ALTERNATIVE?"
In SYSTEMS ANALYSIS, a DECISION MAKER is often concerned with
the probability that a project (the chosen alternative) cannot be
carried out with the time and money available. This risk of
failure may differ from alternative to alternative and should be
estimated as part of the analysis.

In another usage, risk
means an uncertain and strongly adverse IMPACT, as in "the risks
of nuclear power plants to the population are..." In that case,
risk analysis or RISK ASSESSMENT] is a study composed of two
parts, the first dealing with the identification of the strongly
adverse impacts, and the second with determination of their
respective probabilities. (IIASA)

ROLE-PLAYING

A type of SIMULATION in which persons (referred
to as actors or players), sometimes with the aid of computers,
act out roles as parts of the system being analyzed. For
example, experts in different fields may be called upon to
simulate the behavior (to predict the response) of specific
segments of a regional or national economy being studied. A
role-playing simulation in which the actors (players) act out
roles as DECISION MAKERS is called GAMING. In gaming, the
players usually have different and conflicting OBJECTIVES (in
business gaming and war gaming, for example). The players may
act as individuals or may be combined into coalitions, or
opposing teams. (IIASA)

SAFE FAIL

a property of a system which can recover from
failure.

SATISFICING

Satisficing is an alternative to OPTIMIZATION for
cases where there are MULTIPLE and COMPETITIVE OBJECTIVES in
which one gives up the idea of obtaining a "best" solution. In
this approach one sets lower bounds for the various objectives
that, if attained, will be "good enough" and then seeks a
solution that will exceed these bounds. The satisficer's
philosophy is that in real-world problems there are too many
uncertainties and conflicts in values for there to be any hope of
obtaining a true optimization and that it is far more sensible to
set out to do "well enough" (but better than has been done
previously). (IIASA)

SCENARIO

A scenario is an outline of an hypothesized chain of
events. The term is used to denote:

a FORECAST based on loose
assumptions rather than on a more formal inference from the past
or

a synopsis of a proposed COURSE OF ACTION. (IIASA)

a
sequence of possible events to be studied in a system of
interest. (Arbib)

SCHEMA

A person's point of view on some set of issues which
greatly determines the way he or she responds to them. (Arbib)

SCIENTIFIC METHOD

a sequence of procedures intended to
produce agreement among a set of observers, for example:

Define a problem,

Gather pertinent data,

Form a working
hypothesis or explanation,

Do experiments to test the
hypothesis,

Interpret the results,

Draw a conclusion and
modify the hypothesis as needed.

SECOND LAW OF THERMODYNAMICS

elements in a closed system tend
to seek their most probable distribution; in a closed system
entropy always increases. The paraphrases below were compiled by
Heinz Von Foerster.

Clausius (l822-l888) It is impossible that, at the end
of a cycle of changes, heat has been transferred from a colder to
a hotter body without at the same time converting a certain
amount of work into heat.

Lord Kelvin (l824-l907) In a cycle of processes, it is
impossible to transfer heat from a heat reservoir and convert it
all into work, without at the same time transferring a certain
amount of heat from a hotter to a colder body.

Ludwig Boltzmann (l844-l906) For an adiabatically
enclosed system, the entropy can never decrease. Therefore, a
high level of organization is very improbable.

Max Plank (l858-l947) A perpetual motion machine of the
second kind is impossible.

Caratheodory (l885-l955) Arbitrarily near to any given
state there exist states which cannot be reached by means of
adiabatic processes.

(From Sears and Zemansky): 100% conversion of heat into
mechanical work is not possible by any form of engine. (p. 342)
There is a tendency in nature to proceed toward a state of
greater molecular disorder. This one-sidedness of nature
produces irreversible processes. (p. 347)

SECONDARY DECISION

Secondary decisions are those choices made
by the analyst that determine the way in which SYSTEMS ANALYSIS
of a given problem or issue will be performed. They include
making the simplifying assumptions by which a complex issue will
be made tractable in analysis, choosing the forms of MODELS,
selecting the techniques of computation and SIMULATION, deciding
what data have to be acquired, judging what support by experts of
various disciplines to use in performing the analysis, and so on.

The secondary decisions are distinguished from PRIMARY
DECISIONS, that is, the decisions to be taken by the DECISION
MAKER and related to the object problem or issue to which a
systems analysis is applied. (IIASA)

SELECTION

a process of differential realization of a
production of unities in a context that specifies the unitary
organization that can be realized. In a population of
autopoietic unities, selection is a process of differential
realization of autopoiesis, and hence, of differential
self-production. (Maturana and Varela, 1979)

SELF-CONSCIOUSNESS

the domain of self-observation. (Maturana
and Varela, 1979)

SELF-ORGANIZING

St Thomas Aquinas was probably the most
influential Christian thinker. He constructed logical proofs of
the existence of God. One of these proofs referred to God as the
ultimate organizer or designer. The argument was that everything
had to be organized and this called for an organizer. In turn,
the organizer had to be organized and so on back the original
organizer who had to have existed from eternity: this was God. If
something is organized we tend to feel that an outside influence
must have organized it at some time. But it need not be so. The
concept of a self-organizing system is important because it now
seems that life itself came about through a self-organizing
process whereby different chemicals came together in a more or
less chance fashion and gradually organized themselves into
living patterns. Of course, it may still be argued that there
was a need for God to organize the chemicals in such a way that
they could become self-organizing.

A chain made out of paper clips suggests that someone has
taken the trouble to link paper clips together to make a chain.
It is not in the nature of paper clips to make themselves up into
a chain. But, if you take a number of paper clips, open them up
slightly and then shake them all together in a cocktail shaker,
you will find at the end that the clips have organized themselves
into short or long chains. The chains are not so neat as chains
put together by hand but, nevertheless, they are chains. A
teacher can organize her class into groups by assigning each
child to a specific group and picking the group leaders. She
could also tell the children to organize themselves into groups
of five and then let them get on with it in a self-organizing
fashion. The diagram shows an object that has a magnet out on a
prong (bottom of a Y) and two metal plates on the bulb (top of a
Y). If we shake up a number of these objects we find that they
tend to organize themselves into the arrangement shown. Once the
magnet comes into contact with the metal plate it tends to stick
there. In other words once something has happened, it does not
un-happen so easily. It is this asymmetry that is the basis of
self-organization. In the way our mind deals with the outside
world in terms of perception we can find a self-organizing
system. (De Bono) See also PRINCIPLE OF SELF-ORGANIZATION.

Y Y
Y
Y
Y Y
Y
Y
Y Y
Y

SELF-ORGANIZINGSYSTEM

The concept of a self-organizing
system has changed over time. In the early days it was defined
as a system which changes its basic structure as a function of
its experience and environment. The term appears to have been
used first by Farley and Clark of Lincoln Laboratory in l954 in
their paper in the Transactions of the Institute of Radio
Engineers, Professional Group on Information Theory. (Marshall C.
Yovits, 1962, Preface) However, it is important to note that an
organism does not organize itself independent of its environment.
Von Foerster persuasively argued that only organisms and their
environments taken together organize themselves. (Von Foerster,
1960). Ashby redefined a self-organizing system to be not an
organism that changes its structure as a function of its
experience and environment but rather the system consisting of
the organism and environment taken together. (Ashby, 1960)

SELF-REPRODUCTION

when a unity produces another with a
similar organization to its own, through a process that is
coupled to the process of its own specifications. Only
autopoietic systems can self-reproduce. (Maturana and Varela,
1979)

SENSITIVITY ANALYSIS

A procedure to determine the sensitivity
of the outcomes of an ALTERNATIVE to changes in its parameters
(as opposed to changes in the ENVIRONMENT; see CONTINGENCY
ANALYSIS, A FORTIORI ANALYSIS). If a small change in a parameter
results in relatively large changes in the outcomes, the outcomes
are said to be sensitive to that parameter. This may mean that
the parameter has to be determined very accurately or that the
alternative has to be redesigned for low sensitivity. (IIASA)

SHANNON'S TENTH THEOREM

"If the correction channel has a
capability equal to Hy(x) (the amount of additional information
that must be supplied per second at the receiving point to
correct the received message), it is possible to so encode the
correction data as to send it over this channel and correct all
but an arbitrarily small fraction of the errors. This is not
possible if the channel capacity is less than Hy(x)." (Shannon
and Weaver, 1948, p. 68)

SIMULATION

the operation of a dynamic model in order to
obtain a sequence of?utcomes that could occur in a real world
system. Simulations of social processes can be accomplished
either by human player games or by computer programs or by a
combination of the two. Rather than simple computing the
solution to a set of equations, a simulation produces a synthetic
history oh the process. Beginning with a set of initial
conditions, the simulation plays through the various kinds of
events which might occur.

Simulation is the term applied to
the process of modeling the essential features of a situation and
then predicting what is likely to happen by operating with the
MODEL cace by case--i.e., by estimating the results of proposed
actions from a series of imaginary experiments (imaginary because
they are performed on the representation of the situation, the
model, rather than on the situation itself). Most frequently,
the simulation is a [COMPUTER SIMULATION] in which the
representation is carried out numerically on a digital computer.
It may also be done on an analogue computer or by means of a
physical representation, say by a wooden airfoil in a wind
tunnel. [MAN-MACHINE SIMULATION] is a simulation that employs a
MAN-MACHINE MODEL.

Also see: ROLE PLAYING, GAMING. (IIASA)

SIZE PRINCIPLE

In n-person, zero-sum games, where side
payments are permitted, where players are rational, and where
they have perfect information, only minimum winning coalitions
occur. In social situations similar to n-person, zero-sum games
with side payments, participants create coalitions just as large
as they believe will ensure winning and no larger. (Wm. Riker,
p. 32)

SPECIALIZATION

In a system consisting of elements with roughly
equal and constant CHANNEL CAPACITY (information processing
capability), an increase in the channel capacity of the system
requires specialization of the tasks performed by each element.

SPECIES

a population or collection of populations of
reproductively interconnected individuals which, thus, are nodes
in a historical network. (Maturana and Varela, 1979)

STABILITY

the tendency of the variables or components of a
system to remain within defined and recognizable limits despite
the impact of disturbances. (Young, p. l09)

STABILITY

(expanded or global stability) The ability of a
system to persist and to remain qualitatively unchanged in
response either to a disturbance or to fluctuations of the system
caused by a disturbance. This idea of stability combines the
concepts of traditional stability and Holling's new concept of
RESILIENCE. (Holling)

STABILITY

The capacity of an object or system to return to
equilibrium after having been displaced. Note with two possible
kinds of equilibrium one may have a static (linear) stability of
rest or a dynamic (nonlinear) stability of an endlessly repeated
motion. (Iberall)

STABILITY

a system is stable if, when perturbed, it returns to
its original state. The more quickly it returns, the more stable
it is.

STATE

The state of a system at a given instant is the set of
numerical values which its variables have at that instant.
(Ashby, l960, p. l6)

STATE-DETERMINED SYSTEM

a system whose path and/or final state
are uniquely determined by the initial state of the system
regardless of the way in which the initial state came into being.
(Young, p. ll0)

STATE-DETERMINED SYSTEM

a concept that is central to the
theory of mechanism. If a set of variables is state-determined,
and we elicit its canonical representation by primary operations,
then our knowledge of that system is COMPLETE. It is certainly
not a complete knowledge of the real "machine" that provides the
system, for this is probably inexhaustible; but it IS complete
knowledge of the system abstracted--complete in the sense that as
our predictions are now single-valued and verified, they have
reached (a local) finality. If a tipster names a single horse
for each race, and if his horse always win, then though he may be
an ignorant man in other respects, we would have to admit that
his knowledge in this one respect was complete. Because
knowledge of the state-determined system is complete and maximal,
all the other branches of the theory of mechanism, which treat of
what happens in other cases, must be obtainable from this central
case as variations on the question: what if my knowledge is
incomplete in the following way...? (Ashby, l960, p. 270)

STATE OF THE WORLD

State of the world in connection with a
COURSE OF ACTION means the aggregate of natural, economic,
social, cultural, and other conditions on which the presumed
CONSEQUENCES must depend and to which the course of action must
be matched. A FORECAST of the state of the world is required to
predict the results of any course of action. See
ENVIRONMENT.(IIASA)

STATES

the raw data of cybernetics; aspects, features,
qualities, attributes, properties. classifications; the
observables, distinguishables. States may be either unanalyzed
or analyzed; if the former, they may be represented by single
symbols; if the latter, they may be represented by compound
symbols or vectors. For those who demand that a state be a state
OF something, we may redefine STATE as any aspect, feature, etc.,
of a NOMINAL ENTITY, that may change without impairing the
identity of the nominal entity. This, in turn, requires that we
define a nominal entity as any object of discourse; anything with
sufficient coherence and persistence to be treated as an isolate
in discourse; anything capable of interpersonal reference;
anything graspable by the tongs of language. A system is then
seen as a formalization of a nominal entity by the specification
of a set of states of the entity. (George W. Zopf, Jr.in
Handout by Ashby, 1961)

STATICAL PHENOMENOLOGY

the phenomenology generated by the
relations between properties of components. (Maturana and Varela,
1979)

STOCHASTIC

partially random or uncertain, not continuous; a
stochastic variable is neither completely determined nor
completely random; in other words, it contains an element of
probability. A system containing one or more stochastic
variables is probabilistically determined. (Ithiel Pool)

STRUCTURE

the actual relations which hold between the
components which integrate a concrete machine in a given space.
(Maturana and Varela, 1979)

SUBOPTIMIZATION

Suboptimization refers to the analysis to
assist a lower level decision as a step toward the attainment of
a higher level objective to which the lower level decision is to
contribute. Thus, an OPTIMIZATION of a city's streetcar
operations would be a suboptimization if the higher level aim is
to optimize the entire public transportation system.
Analysts and decision makers must always suboptimize--that is,
consider actions that pertain to only part of the elements that
enter a problem--neglecting some things and fixing other
arbitrarily. Even if all suboptimization problems relevant for a
higher level problem are successfully solved, this will not mean,
usually, that the higher level problem will be optimized. One
could usually do better by treating all partial problems and
their interrelationships simultaneously. (IIASA)

SYNERGISTICORSYNERGETIC

A synergistic system is nonlinear.
In a synergistic system, summing previously separate inputs
produces an output which is greater than or different from the
sum of the separate outputs.

SYSTEM

a set of variables selected by an observer.
(Ashby, 1960)

Usually three distinctions are made: 1. An
observed object. 2. A perception of an observed object. This
will be different for different observers. 3. A model or
representation of a perceived object. A single observer can
construct more than one model or representation of a single
object. Some people assume that 1. and 2. are the same. This
assumption can lead to difficulties in communication. Usually
the term "system" is used to refer to either 1. or 2. "Model"
usually refers to 3. Ashby used the terms "machine," "system,"
and "model" in that order for the three distinctions. (Umpleby)

a set or arrangement of entities so related or connected so
as to form a unity or organic whole. (Iberall)

Any
definable set of components. (Maturana and Varela, 1979)

SYSTEMS ANALYSIS

This term has many different meanings. In
the sense adopted for the Handbook, systems analysis is an
explicit formal inquiry carried out to help someone (referred to
as the DECISION MAKER) identify a better COURSE OF ACTION and
make a better decision than he might otherwise have made. The
characteristic attributes of a problem situation where systems
analysis is called upon are complexity of the issue and
uncertainty of the outcome of any course of action that might
reasonably be taken. Systems analysis usually has some
combination of the following: identification and
re-identification) of OBJECTIVES, CONSTRAINTS, and alternative
courses of action; examination of the probable CONSEQUENCES of
the alternatives in terms of costs, benefits, and RISKS;
presentation of the results in a comparative framework so that
the decision maker can make an informed choice from among the
alternatives. The typical use of systems analysis is to guide
decisions on issues such as national or corporate plans and
programs, resource use and protection policies, research and
development in technology, regional and urban development,
educational systems, and?alth and other social services.
Clearly, the nature of these problems requires an
interdisciplinary approach. There are several specific kinds or
focuses of systems analysis for which different terms are used:
A systems analysis related to public decisions is often referred
to as a POLICY ANALYSIS (in the United States the terms are used
interchangeably). A systems analysis that concentrates on
comparison and ranking of alternatives on basis of their known
characteristics is referred to as DECISION ANALYSIS.

That part or aspect of systems analysis that concentrates on
finding out whether an intended course of action violates any
constraints is referred to as FEASIBILITY ANALYSIS. A systems
analysis in which the alternatives are ranked in terms of
effectiveness for fixed cost or in terms of cost for equal
effectiveness is referred to as COST-EFECTIVENESS ANALYSIS.
COST- BENEFIT ANALYSIS is a study where for each alternative the
time stream of costs and the time stream of benefits (both in
monetary units) are discounted (se?DISCOUNT RATE) to yield their
present values. The comparison and ranking are made in terms of
net benefits (benefits minus cost) or the ratio of benefits to
costs. In RISK-BENEFIT ANALYSIS , cost (in monetary units) is
assigned to each risk so as to make possible a comparison of the
discounted sum of these costs (and of other costs as well) with
the discounted sum of benefits that are predicted to result from
the decision. The risks considered are usually events whose
probability of occurrence is low, but whose adverse consequences
would be important (e.g., events such as an earthquake or
explosion of a plant). See: OPERATIONS RESEARCH (IIASA)

SYSTEMS ENGINEERING

The systematic application of engineering
to solutions of a complete problem in its full environment by
systematic assembly and matching of parts in the context of the
lifetime use of the system. (Iberall)

TECHNOLOGY

an object or sequence of operations created by man
to assist in achieving some goal. A technology is a body of
human knowledge that can be passed along from one place to
another and from one generation to the next. Examples of
technologies are: a bow and arrow; a birth control pill; a
nuclear reactor; a legislature; and a planning, programming,
budgeting system of accounting.

TELEOLOGY

the philosophical study of manifestations of design
or purposes in natural processes or occurrences, under the belief
that natural processes are not determined by mechanism but rather
by their utility in an overall natural design. Dysteleology is
the doctrine of purposelessness in nature. (American Heritage
Dictionary) Teleology is associated with vitalism. It explains
apparently purposeful animal behavior by saying that the action
is performed because it will later be advantageous to the animal.
Science, on the other hand, has sought to explain apparently
purposeful behavior through the theory of mechanism. The notion
that an organism contains a model of the actual world and a model
of the desired world and acts so as to make the actual world
conform to the desired world is compatible with the theory of
mechanism. (Umpleby)

TELEONOMY

the element of apparent purpose or possession of a
project in the organization of living systems, without implying
any vitalistic connotations. Frequently considered as a
necessary if not sufficient defining feature of the living
organization. (Maturana and Varela, 1979)

THEORY

An imaginative formulation of apparent relationships or
underlying principles of certain observed phenomena. It may have
been verified to some extent, or it may be pure hypothesis or
conjecture. (Iberall)

TRADE-OFF

Trade-off means an exchange of one quality or thing
for another. Thus, in comparing alternative configurations for
transport aircraft, it may be possible to trade off speed for
payload and still maintain the same total transport capability
per month in the system. In VALUE ANALYSIS and DECISION
THEORY the concept of tradeoffs in the DECISION MAKER'S
preferences is used extensively as a basis for establishing
MULTIATTRIBUTE VALUE FUNCTIONS and MULTIATTRIBUTE UTILITY
FUNCTIONS. See: VALUE, UTILITY (IIASA)

ULTRASTABILITY

the ability to modify internal relationships
and/or to influence environmental conditions in the interests of
neutralizing actual or potential obstacles to the maintenance of
stability. (Young, p. ll0)

ULTRASTABLESYSTEM

a term developed by Ashby and defined by
him as follows: Two systems of continuous variables (that we
called 'environment' and 'reacting part') interact, so that a
primary feedback (through complex sensory and motor channels)
exists between them. Another feedback, working intermittently
and at a much slower order of speed, goes from the environment to
certain continuous variables which in their turn affect some
step-mechanisms, the effect being that the step-mechanisms change
value when and only when these variables pass outside given
limits. The step-mechanisms affect the reacting part; by acting
as parameters to it, they determine how it shall react to the
environment.

We can now appreciate how different an ultrastable system is
from a simple system when the conditions allow the difference to
show clearly. The difference can best be shown by an example.
The automatic pilot is a device which, amongst other actions,
keeps the airplane horizontal. It must, therefore, be connected
to the ailerons in such a way that when the plane rolls to the
right, its output must act on them so as to roll the plane to the
left. If properly joined, the whole system is stable and
self-correcting: it can now fly safely through turbulent air for,
though it will roll frequently, it will always come back to the
level. The Homeostat, if joined in this way, would tend to do
the same. (Though not well suited, it would, in principle, if
given a gyroscope, be able to correct roll.) So far, after a
small disturbance; but connect the ailerons in reverse and
compare them. The automatic pilot would act, after a small
disturbance, to INCREASE the roll and would persist in its wrong
action to the very end. The Homeostat, however, would persist in
its wrong action only until the increasing deviation made the
step-mechanisms start changing. On the occurrence of the first
suitable new value, the Homeostat would act to stabilize instead
of to overthrow; it would return the plane to the horizontal; and
it would then be ordinarily self-correcting for disturbances.
There is therefore some justification for the name 'ultrastable';
for if the main variables are assembled so as to make their field
unstable, the ultrastable system will change this field till it
is stable. The degree of stability shown is therefore of an
order higher than that of the system with a single field.
(Ashby, l960, pp. 98, l08)

UNCERTAINTY

a measure of variety such that uncertainty (H) is
zero when all elements are in the same category. H increases with
both the number of categories and their equiprobability. The
uncertainty resulting from two or more sets of categories is the
sum of the uncertainties of the sets of categories taken
independently. H = the sum of P sub i times the log of P sub i,
where P sub i is the probability of an element being in the Its
category. Since the categories must be specified by an observer,
the uncertainty of a system may be different as seen by different
observers.

UNCERTAINTY

Because of an unfortunate use of terminology in
systems analysis discourse, the word "uncertainty" has both a
precise technical meaning and its loose natural meaning of an
event or situation that is not certain.

In DECISION THEORY and statistics, a precise distinction is
made between a situation of RISK and one of certainty. There is
an uncontrollable random event inherent in both of these
situations. The distinction is that in a risky situation the
uncontrollable random event comes from a known probability
distribution, whereas in an uncertain situation the probability
distribution is unknown. (IIASA)

UNITY

that which is distinguishable from a background, the
sole condition necessary for existence in a given domain. The
nature of a unity and the domain in which the unity exists are
specified by the process of its distinction and determination;
this is so regardless of whether this process is conceptual or
physical. (Maturana and Varela, 1979)

UTILITY

In economics, utility means the real or fancied
ability of a good or service to satisfy a human want. An
associated term is WELFARE FUNCTION (synonym: utility
function--not to be confused with UTILITY FUNCTION in DECISION
THEORY; see below), which relates the utility derived by an
individual or group to the goods and services that it consumes.
MARGINAL UTILITY is the change in utility due to a one unit
change in the quantity of a good or service consumed.

In
DECISION THEORY, utility is a measure of the desirability of
CONSEQUENCES of courses of action that applies to decision making
under RISK--that IS, under UNCERTAINTY with known probabilities.

The concept of utility applies to both SINGLE-ATTRIBUTE and
MULTIATTRIBUTE CONSEQUENCES. The fundamental assumption in
UTILITY THEORY is that the DECISION MAKER always chooses the
ALTERNATIVE for which the expected value of the utility (EXPECTED
UTILITY) is maximum. If that assumption is accepted, utility
theory can be used to predict or prescribe the choice that the
decision maker will make, or should make, among the available
alternatives. For that purpose, a utility has to be assigned to
each of the possible (and mutually exclusive) consequences of
every alternative. A UTILITY FUNCTION is the rule by which this
assignment is done and depends on the preferences of the
individual decision maker. In utility theory, the utility
measures u of the consequences are assumed to reflect a decision
maker's preferences in the following sense: (i) the numerical
order of utilities for consequences preserves the decision
maker's preference order among the consequences; (ii) the
numerical order of expected utilities of alternatives (referred
to, in utility theory, as gambles or lotteries) preserves the
decision maker's preference order among these alternatives
(lotteries). For example if alternative A can have three
mutually exclusive consequences, x,y,z, and the decision maker
prefers z to y and x to z, the utilities Ul, U2, U3
assigned to x,y,z must be such that U3)U2)U1. If the
probabilities of the consequences x,y,z are P1,P2,1-p1,-p2,
respectively, the expected utility of alternative A is calculated
as

E(u/P) = PlUl + P2U2 + (l-Pl-P2)U3

where P means the probability distribution, characteristic for
the alternative (i.P1, P2, 1-P1-P2). (IIASA) If the decision
maker prefers alternative B, which has probability distribution
Q, to alternative A, the utility assignments in both alternatives
must be such that

E(u/Q) 1/2 > E(u/P).

Utility theory provides a basis for the assignment of utilities
to consequences by formulating necessary and sufficient
conditions to satisfy (i) and (ii). A utility function is
defined mathematically as a function u(.) from the set of
consequences Y into the real numbers that provides for
satisfaction of (i) and (ii). There exist various methods for
constructing utility functions. The best-known method is based
on indifference judgments of the decision maker about specially
constructed alternatives(lotteries). Utility theory permits one
to distinguish RISK-PRONE, RISK- NEUTRAL and RISK-AVERSE
DECISION MAKERS. For example, if the mutually exclusive payoffs
xl,x2,x3 of an alternative A are all expressed in the same units
(e.g., schillings), the decision maker is risk-prone if he
prefers the alternative A (prefers the lottery) to receiving,
with no risk, the expected value of the payoffs (calculated
directly as

E(x/P) = plxl + p2x2 + (l-pl-p2)x3).

This preference can also be expressed as

E(u/P) > u(E(x/P))

i.e., the expected utility of the lottery to the risk-prone
decision maker is larger than the utility of the expected value
of the consequence. The risk-neutral and risk-averse decision
makers are defined accordingly. The MULTIATTRIBUTE UTILITY
FUNCTION is defined as a function u(.) from the set of
multiattribute consequences into the real numbers. This means
that it applies to cases where each of the mutually exclusive
consequences has several attributes. Multiattribute utility
functions, besides having properties (i) and (ii), also express
the decision maker's TRADE OFFS among the attributes (compare
MULTIATTRIBUTE VALUE FUNCTION). Several special forms of
multiattribute utility functions have been developed, including
the additive and the multiplicative forms. (IIASA)

VALIDATION

the process of determining how well one system
replicates properties of some other system or, more generally,
any comparison between the representation of a system and
specified criteria. The validation of an operating model cannot
be separated from the purpose for which it is designed and used.

VALIDATION

Validation is the process of increasing the
confidence that the outputs of the model conform to reality in
the required range. In some cases, the model's output can be
compared to data from historical sources or from an experiment
conducted for?lidation. A model can never be completely
validated. We can never prove that its results conform to
reality in all respects. It can only be invalidated. Predictive
models be validated only by judgment, since a model may fit past
data well without having good predictive qualities. (IIASA)

VALUE

Value can be either objective or subjective. In the
latter case, it means subjective worth or importance. For
example, "the value of future benefits to the DECISION MAKER,"
"the value of clean air to the society." For the purposes of
analysis, the subjective values must be measured on some scale.
These measures of value should be based on preferences expressed
by the person or group of interest.

In [VALUE ANALYSIS,] one considers that the value v is
related to the physical or other objective measure y of a
consequence by a subjectively defined [VALUE FUNCTION,] so that v
= f(y). A value function usually departs from proportionality,
i.e.,it usually is a nonlinear dependence. A typical example is
the subjective value of money to an individual: the first l,000
schillings in his savings account are probably of more value to
him that the l,000 schillings that would increase the state oh
his account from 100,000 to 101,000 schillings. The value of a
multiattribute consequence with VALUE-RE?ANT ATTRIBUTES
y1,y2,..yn can be expressed by a MULTIATTRIBUTE VALUE FUNCTION,
v(yl,y2,..yn). A multiattribute value function must satisfy
the following condition:

v(yl,y2,...yn) is greater than or equal to v(y'l,y'2,...y'n)

if and only if the multiattribute consequence (yl,y2,..yn) is
preferred or indifferent to (y'1,y'2,...y'n).

Several theories exist according to which a multiattribute
value function V(.) can, in appropriate cases, be expressed as an
aggregate of single-attribute functions Vi(.). For example, the
additive [CONJOINT MEASUREMENT THEORY] assumes that

n
v(yl,y2,....,yn) = SUM Vi(yi).
i=l

See also: UTILITY, DECISION THEORY (IIASA)

VARIABLE

a measurable quantity which at every instant has a
definite numerical value. If there is any doubt whether a
particular quantity may be admitted as a variable, use the
criterion whether it can be represented by a pointer on a dial.
Pressure, angle, electric potential, volume, velocity, mass,
viscosity, population, national income per capita and time
itself, to mention only a few, can all be specified numerically
and recorded on dials. Eddington's statement on the subject is
explicit: "The whole subject matter of exact science consists of
pointer readings and similar indications. Whatever quantity we
say we are 'observing', the actual procedure nearly always ends
in reading the pointer of some kind of indicator on a graduated
scale or its equivalent." (Ashby, 1960, p. l5)

VARIETY

in relation to a set of distinguishable elements,
either (l) the number of distinct elements, or

the logarithm
to the base 2 of that number, the context indicating the sense
used. When variety is measured in the logarithmic form, its unit
is the "bit," a contraction of "BInary digiT." (Ashby, 1956, P.
126)

VARIETY

the amount of output from a system is limited by the
variety possible within the system and/or the variety of input to
the system. The number of possible alternative communications
between the two systems is limited by that system having the
fewest output alternatives and/or the fewest input alternatives.
(Charles E. Osgood)

VERIFICATION

A (computer) MODEL is said to be verified if it
behaves in the way that the model builder wanted it to behave.
This means that the instructions are correct and have been
properly programmed. One check for verification is to hold some
of the variables constant to determine whether the output changes
in anticipated ways as other variables are changed. Another
typical check is to test how the model behaves in limit
situations. Compare: VALIDATION (IIASA)